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"source": [
"# Scikit-Learn\n",
"\n",
"Taken from [**Python Data Science Handbook**](https://www.oreilly.com/library/view/python-data-science/9781491912126/) by Jake VanderPlas. \n",
"Probably the most comprehensive material one can find on Scikit-learn is provided here."
]
},
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"There are several Python libraries that provide solid implementations of a range of machine learning algorithms.\n",
"One of the best known is [Scikit-Learn](http://scikit-learn.org), a package that provides efficient versions of a large number of common algorithms.\n",
"Scikit-Learn is characterized by a clean, uniform, and streamlined API, as well as by very useful and complete online documentation.\n",
"A benefit of this uniformity is that once you understand the basic use and syntax of Scikit-Learn for one type of model, switching to a new model or algorithm is straightforward.\n",
"\n",
"We will start by covering data representation in Scikit-Learn, then delve into the Estimator API, and finally go through a more interesting example of using these tools for exploring a set of images of handwritten digits."
]
},
{
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"source": [
"## Data Representation in Scikit-Learn"
]
},
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"source": [
"Machine learning is about creating models from data: for that reason, we'll start by discussing how data can be represented.\n",
"The best way to think about data within Scikit-Learn is in terms of *tables*."
]
},
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"source": [
"A basic table is a two-dimensional grid of data, in which the rows represent individual elements of the dataset, and the columns represent quantities related to each of these elements.\n",
"For example, consider the [Iris dataset](https://en.wikipedia.org/wiki/Iris_flower_data_set), famously analyzed by Ronald Fisher in 1936.\n",
"We can download this dataset in the form of a Pandas `DataFrame` using the [Seaborn](http://seaborn.pydata.org/) library, and take a look at the first few items:"
]
},
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species
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"text/plain": [
" sepal_length sepal_width petal_length petal_width species\n",
"0 5.1 3.5 1.4 0.2 setosa\n",
"1 4.9 3.0 1.4 0.2 setosa\n",
"2 4.7 3.2 1.3 0.2 setosa\n",
"3 4.6 3.1 1.5 0.2 setosa\n",
"4 5.0 3.6 1.4 0.2 setosa"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import warnings\n",
"warnings.simplefilter(action='ignore')\n",
"\n",
"import seaborn as sns\n",
"iris = sns.load_dataset('iris')\n",
"iris.head()"
]
},
{
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"Here each row of the data refers to a single observed flower, and the number of rows is the total number of flowers in the dataset.\n",
"In general, we will refer to the rows of the matrix as *samples*, and the number of rows as `n_samples`.\n",
"\n",
"Likewise, each column of the data refers to a particular quantitative piece of information that describes each sample.\n",
"In general, we will refer to the columns of the matrix as *features*, and the number of columns as `n_features`."
]
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"source": [
"### The Features Matrix\n",
"\n",
"The table layout makes clear that the information can be thought of as a two-dimensional numerical array or matrix, which we will call the *features matrix*.\n",
"By convention, this matrix is often stored in a variable named `X`.\n",
"The features matrix is assumed to be two-dimensional, with shape `[n_samples, n_features]`, and is most often contained in a NumPy array or a Pandas `DataFrame`, though some Scikit-Learn models also accept SciPy sparse matrices.\n",
"\n",
"The samples (i.e., rows) always refer to the individual objects described by the dataset.\n",
"For example, a sample might represent a flower, a person, a document, an image, a sound file, a video, an astronomical object, or anything else you can describe with a set of quantitative measurements.\n",
"\n",
"The features (i.e., columns) always refer to the distinct observations that describe each sample in a quantitative manner.\n",
"Features are often real-valued, but may be Boolean or discrete-valued in some cases."
]
},
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"source": [
"### The Target Array\n",
"\n",
"In addition to the feature matrix `X`, we also generally work with a *label* or *target* array, which by convention we will usually call `y`.\n",
"The target array is usually one-dimensional, with length `n_samples`, and is generally contained in a NumPy array or Pandas `Series`.\n",
"The target array may have continuous numerical values, or discrete classes/labels.\n",
"While some Scikit-Learn estimators do handle multiple target values in the form of a two-dimensional, `[n_samples, n_targets]` target array, we will primarily be working with the common case of a one-dimensional target array.\n",
"\n",
"A common point of confusion is how the target array differs from the other feature columns. The distinguishing characteristic of the target array is that it is usually the quantity we want to *predict from the features*: in statistical terms, it is the dependent variable.\n",
"For example, given the preceding data we may wish to construct a model that can predict the species of flower based on the other measurements; in this case, the `species` column would be considered the target array.\n",
"\n",
"With this target array in mind, we can use Seaborn to conveniently visualize the data (see the following figure):"
]
},
{
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",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"import seaborn as sns\n",
"sns.pairplot(iris, hue='species', height=1.5);"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "831rpdhVhBiD"
},
"source": [
"For use in Scikit-Learn, we will extract the features matrix and target array from the `DataFrame`, which we can do using some of the Pandas `DataFrame` operations:"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"deletable": true,
"editable": true,
"id": "1-PkC53DhBiE",
"jupyter": {
"outputs_hidden": false
},
"outputId": "c93853d7-9335-4891-cdaa-5785f61dac64"
},
"outputs": [
{
"data": {
"text/plain": [
"(150, 4)"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X_iris = iris.drop('species', axis=1)\n",
"X_iris.shape"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"deletable": true,
"editable": true,
"id": "TxwrHBVZhBiE",
"jupyter": {
"outputs_hidden": false
},
"outputId": "55f089be-79af-49d2-d6a3-561de6dbd747"
},
"outputs": [
{
"data": {
"text/plain": [
"(150,)"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"y_iris = iris['species']\n",
"y_iris.shape"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "PwLc6jcUhBiF"
},
"source": [
"## The Estimator API"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "dK-zw9OIhBiF"
},
"source": [
"The Scikit-Learn API is designed with the following guiding principles in mind, as outlined in the [Scikit-Learn API paper](http://arxiv.org/abs/1309.0238):\n",
"\n",
"- *Consistency*: All objects share a common interface drawn from a limited set of methods, with consistent documentation.\n",
"\n",
"- *Inspection*: All specified parameter values are exposed as public attributes.\n",
"\n",
"- *Limited object hierarchy*: Only algorithms are represented by Python classes; datasets are represented\n",
" in standard formats (NumPy arrays, Pandas `DataFrame` objects, SciPy sparse matrices) and parameter\n",
" names use standard Python strings.\n",
"\n",
"- *Composition*: Many machine learning tasks can be expressed as sequences of more fundamental algorithms,\n",
" and Scikit-Learn makes use of this wherever possible.\n",
"\n",
"- *Sensible defaults*: When models require user-specified parameters, the library defines an appropriate default value.\n",
"\n",
"In practice, these principles make Scikit-Learn very easy to use, once the basic principles are understood.\n",
"Every machine learning algorithm in Scikit-Learn is implemented via the Estimator API, which provides a consistent interface for a wide range of machine learning applications."
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "dsaRMWWshBiF"
},
"source": [
"### Basics of the API\n",
"\n",
"Most commonly, the steps in using the Scikit-Learn Estimator API are as follows:\n",
"\n",
"1. Choose a class of model by importing the appropriate estimator class from Scikit-Learn.\n",
"2. Choose model hyperparameters by instantiating this class with desired values.\n",
"3. Arrange data into a features matrix and target vector, as outlined earlier in this chapter.\n",
"4. Fit the model to your data by calling the `fit` method of the model instance.\n",
"5. Apply the model to new data:\n",
" - For supervised learning, often we predict labels for unknown data using the `predict` method.\n",
" - For unsupervised learning, we often transform or infer properties of the data using the `transform` or `predict` method.\n",
"\n",
"We will now step through several simple examples of applying supervised and unsupervised learning methods."
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "2ifCVLxuhBiF"
},
"source": [
"### Supervised Learning Example: Simple Linear Regression\n",
"\n",
"As an example of this process, let's consider a simple linear regression—that is, the common case of fitting a line to $(x, y)$ data.\n",
"We will use the following simple data for our regression example (see the following figure):"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"deletable": true,
"editable": true,
"id": "SqtL5kCJhBiF",
"jupyter": {
"outputs_hidden": false
},
"outputId": "a93c0940-5ac9-477a-e72a-57456d78b920"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"\n",
"rng = np.random.RandomState(42)\n",
"x = 10 * rng.rand(50)\n",
"y = 2 * x - 1 + rng.randn(50)\n",
"plt.scatter(x, y);"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "ZwFJKSldhBiF"
},
"source": [
"With this data in place, we can use the recipe outlined earlier. Let's walk through the process:"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "EEdEF1oehBiG"
},
"source": [
"#### 1. Choose a class of model\n",
"\n",
"In Scikit-Learn, every class of model is represented by a Python class.\n",
"So, for example, if we would like to compute a simple `LinearRegression` model, we can import the linear regression class:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"deletable": true,
"editable": true,
"id": "M4OzXLpRhBiG",
"tags": []
},
"outputs": [],
"source": [
"from sklearn.linear_model import LinearRegression"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "21ihfxfxhBiG"
},
"source": [
"Note that other more general linear regression models exist as well; you can read more about them in the [`sklearn.linear_model` module documentation](http://Scikit-Learn.org/stable/modules/linear_model.html)."
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "h3kN-Pv4hBiG"
},
"source": [
"#### 2. Choose model hyperparameters\n",
"\n",
"An important point is that *a class of model is not the same as an instance of a model*.\n",
"\n",
"Once we have decided on our model class, there are still some options open to us.\n",
"Depending on the model class we are working with, we might need to answer one or more questions like the following:\n",
"\n",
"- Would we like to fit for the offset (i.e., *y*-intercept)?\n",
"- Would we like the model to be normalized?\n",
"- Would we like to preprocess our features to add model flexibility?\n",
"- What degree of regularization would we like to use in our model?\n",
"- How many model components would we like to use?\n",
"\n",
"These are examples of the important choices that must be made *once the model class is selected*.\n",
"These choices are often represented as *hyperparameters*, or parameters that must be set before the model is fit to data.\n",
"In Scikit-Learn, hyperparameters are chosen by passing values at model instantiation.\n",
"\n",
"For our linear regression example, we can instantiate the `LinearRegression` class and specify that we would like to fit the intercept using the `fit_intercept` hyperparameter:"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"deletable": true,
"editable": true,
"id": "GJjC9ifohBiG",
"jupyter": {
"outputs_hidden": false
},
"outputId": "8d5c0a27-e75b-42f7-8f4e-40b2a29c15c4"
},
"outputs": [
{
"data": {
"text/html": [
"
LinearRegression()
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
LinearRegression()
"
],
"text/plain": [
"LinearRegression()"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"model = LinearRegression(fit_intercept=True)\n",
"model"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "t-hnYB38hBiH"
},
"source": [
"Keep in mind that when the model is instantiated, the only action is the storing of these hyperparameter values.\n",
"In particular, we have not yet applied the model to any data: the Scikit-Learn API makes very clear the distinction between *choice of model* and *application of model to data*."
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "gvjNmhjUhBiH"
},
"source": [
"#### 3. Arrange data into a features matrix and target vector\n",
"\n",
"Previously we examined the Scikit-Learn data representation, which requires a two-dimensional features matrix and a one-dimensional target array.\n",
"Here our target variable `y` is already in the correct form (a length-`n_samples` array), but we need to massage the data `x` to make it a matrix of size `[n_samples, n_features]`.\n",
"In this case, this amounts to a simple reshaping of the one-dimensional array:"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(50,)"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"x.shape"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"deletable": true,
"editable": true,
"id": "QvDH8P7ghBiH",
"jupyter": {
"outputs_hidden": false
},
"outputId": "d8cd641e-0ee6-4e02-8bf3-a84dc1989db2"
},
"outputs": [
{
"data": {
"text/plain": [
"(50, 1)"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X = x[:, np.newaxis]\n",
"X.shape"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "9oF8VIhrhBiH"
},
"source": [
"#### 4. Fit the model to the data\n",
"\n",
"Now it is time to apply our model to the data.\n",
"This can be done with the `fit` method of the model:"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"deletable": true,
"editable": true,
"id": "Bk7Z8boQhBiH",
"jupyter": {
"outputs_hidden": false
},
"outputId": "70f3dbb4-3d2b-4344-8caa-09300fde0ff8"
},
"outputs": [
{
"data": {
"text/html": [
"
LinearRegression()
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
LinearRegression()
"
],
"text/plain": [
"LinearRegression()"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"model.fit(X, y)"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "kUENI9dehBiH"
},
"source": [
"This `fit` command causes a number of model-dependent internal computations to take place, and the results of these computations are stored in model-specific attributes that the user can explore.\n",
"In Scikit-Learn, by convention all model parameters that were learned during the `fit` process have trailing underscores; for example in this linear model, we have the following:"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"deletable": true,
"editable": true,
"id": "q9R3w9FlhBiH",
"jupyter": {
"outputs_hidden": false
},
"outputId": "b0237448-07cf-4aee-af27-f20e10ad5604"
},
"outputs": [
{
"data": {
"text/plain": [
"array([1.9776566])"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"model.coef_"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"deletable": true,
"editable": true,
"id": "fms_TlqqhBiH",
"jupyter": {
"outputs_hidden": false
},
"outputId": "7ec1075c-a858-4183-b8ee-c5c7cfa4f447"
},
"outputs": [
{
"data": {
"text/plain": [
"-0.903310725531111"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"model.intercept_"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "Yb_gpGw4hBiI"
},
"source": [
"These two parameters represent the slope and intercept of the simple linear fit to the data.\n",
"Comparing the results to the data definition, we see that they are close to the values used to generate the data: a slope of 2 and intercept of –1.\n",
"\n",
"One question that frequently comes up regards the uncertainty in such internal model parameters.\n",
"In general, Scikit-Learn does not provide tools to draw conclusions from internal model parameters themselves: interpreting model parameters is much more a *statistical modeling* question than a *machine learning* question.\n",
"Machine learning instead focuses on what the model *predicts*.\n",
"If you would like to dive into the meaning of fit parameters within the model, other tools are available, including the [`statsmodels` Python package](http://statsmodels.sourceforge.net/)."
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "JTwirvxyhBiI"
},
"source": [
"#### 5. Predict labels for unknown data\n",
"\n",
"Once the model is trained, the main task of supervised machine learning is to evaluate it based on what it says about new data that was not part of the training set.\n",
"In Scikit-Learn, this can be done using the `predict` method.\n",
"For the sake of this example, our \"new data\" will be a grid of *x* values, and we will ask what *y* values the model predicts:"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"deletable": true,
"editable": true,
"id": "QCnwI6jjhBiI",
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"array([-1. , -0.75510204, -0.51020408, -0.26530612, -0.02040816,\n",
" 0.2244898 , 0.46938776, 0.71428571, 0.95918367, 1.20408163,\n",
" 1.44897959, 1.69387755, 1.93877551, 2.18367347, 2.42857143,\n",
" 2.67346939, 2.91836735, 3.16326531, 3.40816327, 3.65306122,\n",
" 3.89795918, 4.14285714, 4.3877551 , 4.63265306, 4.87755102,\n",
" 5.12244898, 5.36734694, 5.6122449 , 5.85714286, 6.10204082,\n",
" 6.34693878, 6.59183673, 6.83673469, 7.08163265, 7.32653061,\n",
" 7.57142857, 7.81632653, 8.06122449, 8.30612245, 8.55102041,\n",
" 8.79591837, 9.04081633, 9.28571429, 9.53061224, 9.7755102 ,\n",
" 10.02040816, 10.26530612, 10.51020408, 10.75510204, 11. ])"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"xfit = np.linspace(-1, 11)\n",
"xfit"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "IEgsi1AthBiI"
},
"source": [
"As before, we need to coerce these *x* values into a `[n_samples, n_features]` features matrix, after which we can feed it to the model:"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"deletable": true,
"editable": true,
"id": "2XeXiE-rhBiQ",
"jupyter": {
"outputs_hidden": false
}
},
"outputs": [],
"source": [
"Xfit = xfit[:, np.newaxis]\n",
"yfit = model.predict(Xfit)"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "qYnHhgSYhBiR"
},
"source": [
"Finally, let's visualize the results by plotting first the raw data, and then this model fit (see the following figure):"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"deletable": true,
"editable": true,
"id": "g7Pj1ORahBiR",
"jupyter": {
"outputs_hidden": false
},
"outputId": "073c84ab-387d-4c03-9136-a7b3569f38eb"
},
"outputs": [
{
"data": {
"text/plain": [
"[]"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(x, y)\n",
"plt.plot(xfit, yfit, color=\"red\")"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "UO_twlZvhBiR"
},
"source": [
"Typically the efficacy of the model is evaluated by comparing its results to some known baseline, as we will see in the next example."
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "0cHMhuzkhBiS"
},
"source": [
"### Supervised Learning Example: Iris Classification\n",
"\n",
"Let's take a look at another example of this process, using the Iris dataset we discussed earlier.\n",
"Our question will be this: given a model trained on a portion of the Iris data, how well can we predict the remaining labels?\n",
"\n",
"For this task, we will use a simple generative model known as *Gaussian naive Bayes*, which proceeds by assuming each class is drawn from an axis-aligned Gaussian distribution.\n",
"Because it is so fast and has no hyperparameters to choose, Gaussian naive Bayes is often a good model to use as a baseline classification, before exploring whether improvements can be found through more sophisticated models.\n",
"\n",
"We would like to evaluate the model on data it has not seen before, so we will split the data into a *training set* and a *testing set*.\n",
"This could be done by hand, but it is more convenient to use the `train_test_split` utility function:"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"deletable": true,
"editable": true,
"id": "HrXlaFmRhBiS",
"tags": []
},
"outputs": [],
"source": [
"from sklearn.model_selection import train_test_split\n",
"Xtrain, Xtest, ytrain, ytest = train_test_split(X_iris, y_iris,\n",
" random_state=1)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"((112, 4), (112,), (38, 4), (38,))"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Xtrain.shape, ytrain.shape, Xtest.shape, ytest.shape"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "dJTOwNighBiS"
},
"source": [
"With the data arranged, we can follow our recipe to predict the labels:"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"deletable": true,
"editable": true,
"id": "ymY3ckjLhBiS",
"jupyter": {
"outputs_hidden": false
}
},
"outputs": [],
"source": [
"from sklearn.naive_bayes import GaussianNB # 1. choose model class\n",
"model = GaussianNB() # 2. instantiate model\n",
"model.fit(Xtrain, ytrain) # 3. fit model to data\n",
"y_model = model.predict(Xtest) # 4. predict on new data"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(38,)"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"y_model.shape"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "0SwuMulGhBiS"
},
"source": [
"Finally, we can use the ``accuracy_score`` utility to see the fraction of predicted labels that match their true values:"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"deletable": true,
"editable": true,
"id": "fqe_oc4LhBiS",
"jupyter": {
"outputs_hidden": false
},
"outputId": "c866a469-b287-4bae-de39-ca2424a14d79"
},
"outputs": [
{
"data": {
"text/plain": [
"0.9736842105263158"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from sklearn.metrics import accuracy_score\n",
"accuracy_score(ytest, y_model)"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "UorslPF_hBiS"
},
"source": [
"With an accuracy topping 97%, we see that even this very naive classification algorithm is effective for this particular dataset!"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "1wlKy4UHhBiS"
},
"source": [
"### Unsupervised Learning Example: Iris Dimensionality\n",
"\n",
"As an example of an unsupervised learning problem, let's take a look at reducing the dimensionality of the Iris data so as to more easily visualize it.\n",
"Recall that the Iris data is four-dimensional: there are four features recorded for each sample.\n",
"\n",
"The task of dimensionality reduction centers around determining whether there is a suitable lower-dimensional representation that retains the essential features of the data.\n",
"Often dimensionality reduction is used as an aid to visualizing data: after all, it is much easier to plot data in two dimensions than in four dimensions or more!\n",
"\n",
"Here we will use *principal component analysis* (PCA), which is a fast linear dimensionality reduction technique.\n",
"We will ask the model to return two components—that is, a two-dimensional representation of the data.\n",
"\n",
"Following the sequence of steps outlined earlier, we have:"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"deletable": true,
"editable": true,
"id": "8RQ3l1achBiS",
"tags": []
},
"outputs": [],
"source": [
"from sklearn.decomposition import PCA # 1. Choose the model class\n",
"model = PCA(n_components=2) # 2. Instantiate the model\n",
"model.fit(X_iris) # 3. Fit to data\n",
"X_2D = model.transform(X_iris) # 4. Transform the data"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(150, 2)"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X_2D.shape"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "rra9wIzRhBiS"
},
"source": [
"Now let's plot the results. A quick way to do this is to insert the results into the original Iris `DataFrame`, and use Seaborn's `lmplot` to show the results (see the following figure):"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"deletable": true,
"editable": true,
"id": "cL2FHEH7hBiT",
"jupyter": {
"outputs_hidden": false
},
"outputId": "11b48c74-49f3-497a-b0d3-203026686ff5"
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"iris['PCA1'] = X_2D[:, 0]\n",
"iris['PCA2'] = X_2D[:, 1]\n",
"sns.lmplot(x=\"PCA1\", y=\"PCA2\", hue='species', data=iris, fit_reg=False)"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "112bBT41hBiT"
},
"source": [
"We see that in the two-dimensional representation, the species are fairly well separated, even though the PCA algorithm had no knowledge of the species labels!\n",
"This suggests to us that a relatively straightforward classification will probably be effective on the dataset, as we saw before."
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "ny82zW1VhBiT"
},
"source": [
"### Unsupervised Learning Example: Iris Clustering\n",
"\n",
"Let's next look at applying clustering to the Iris data.\n",
"A clustering algorithm attempts to find distinct groups of data without reference to any labels.\n",
"Here we will use a powerful clustering method called a *Gaussian mixture model* (GMM).\n",
"A GMM attempts to model the data as a collection of Gaussian blobs.\n",
"\n",
"We can fit the Gaussian mixture model as follows:"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"deletable": true,
"editable": true,
"id": "VZMfVXkxhBiT",
"jupyter": {
"outputs_hidden": false
}
},
"outputs": [],
"source": [
"from sklearn.mixture import GaussianMixture # 1. Choose the model class\n",
"model = GaussianMixture(n_components=3,\n",
" covariance_type='full') # 2. Instantiate the model\n",
"model.fit(X_iris) # 3. Fit to data\n",
"y_gmm = model.predict(X_iris) # 4. Determine labels"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
" 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
" 2, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
" 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
" 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], dtype=int64)"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"y_gmm"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "cTQEMcd8hBiT"
},
"source": [
"As before, we will add the cluster label to the Iris ``DataFrame`` and use Seaborn to plot the results (see the following figure):"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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sepal_length
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sepal_width
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petal_length
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petal_width
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species
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PCA1
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PCA2
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cluster
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"text/plain": [
" sepal_length sepal_width petal_length petal_width species PCA1 \\\n",
"0 5.1 3.5 1.4 0.2 setosa -2.684126 \n",
"1 4.9 3.0 1.4 0.2 setosa -2.714142 \n",
"2 4.7 3.2 1.3 0.2 setosa -2.888991 \n",
"3 4.6 3.1 1.5 0.2 setosa -2.745343 \n",
"4 5.0 3.6 1.4 0.2 setosa -2.728717 \n",
"\n",
" PCA2 cluster \n",
"0 0.319397 2 \n",
"1 -0.177001 2 \n",
"2 -0.144949 2 \n",
"3 -0.318299 2 \n",
"4 0.326755 2 "
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"iris['cluster'] = y_gmm\n",
"iris.head()"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"deletable": true,
"editable": true,
"id": "AEkfJJw2hBiT",
"jupyter": {
"outputs_hidden": false
},
"outputId": "afe3f58b-c883-4ca8-e8b8-cbb451af1221"
},
"outputs": [
{
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"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.lmplot(x=\"PCA1\", y=\"PCA2\", data=iris, hue='species',\n",
" col='cluster', fit_reg=False);"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "Pv9_bQTihBiT"
},
"source": [
"By splitting the data by cluster number, we see exactly how well the GMM algorithm has recovered the underlying labels: the *setosa* species is separated perfectly within cluster 0, while there remains a small amount of mixing between *versicolor* and *virginica*.\n",
"This means that even without an expert to tell us the species labels of the individual flowers, the measurements of these flowers are distinct enough that we could *automatically* identify the presence of these different groups of species with a simple clustering algorithm!\n",
"This sort of algorithm might further give experts in the field clues as to the relationships between the samples they are observing."
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "bB8Bic2DhBiU"
},
"source": [
"## Application: Exploring Handwritten Digits"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "uHLY2EthhBiU"
},
"source": [
"To demonstrate these principles on a more interesting problem, let's consider one piece of the optical character recognition problem: the identification of handwritten digits.\n",
"In the wild, this problem involves both locating and identifying characters in an image. Here we'll take a shortcut and use Scikit-Learn's set of preformatted digits, which is built into the library."
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "Y49xQjcDhBiU"
},
"source": [
"### Loading and Visualizing the Digits Data\n",
"\n",
"We can use Scikit-Learn's data access interface to take a look at this data:"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"deletable": true,
"editable": true,
"id": "ShW9EkCWhBiU",
"jupyter": {
"outputs_hidden": false
},
"outputId": "cf9ff78b-6d54-4868-b6c0-898cda773f62"
},
"outputs": [
{
"data": {
"text/plain": [
"(1797, 8, 8)"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from sklearn.datasets import load_digits\n",
"digits = load_digits()\n",
"digits.images.shape"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "6ZfIvqPvhBiU"
},
"source": [
"The images data is a three-dimensional array: 1,797 samples each consisting of an 8 × 8 grid of pixels.\n",
"Let's visualize the first hundred of these (see the following figure):"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"deletable": true,
"editable": true,
"id": "BXUKZe89hBiU",
"jupyter": {
"outputs_hidden": false
},
"outputId": "b74eeeef-78d7-42a2-f9c1-08f79299df4a"
},
"outputs": [
{
"data": {
"image/png": 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2foEsNCS0+v8Eb425FbtO7cKSHUuwbJx1my+n7Tm9B2fLz6L/sv7Vj1V6KrGtcBte3fkqLv/uMkKCQxzM0D7NmzRH95bdcfjHw06nYql2rnbXfaLdq1UvrP9qvUMZ2a/wfCG2HNmCdya843Qqtnhm8zOYPXQ2Hun9CACgT9s+KCwuxILtC7T4tLdri67Im5SH8opylFwuQTtXOzz89sPoEq3uYdzQmf7OX2hIKG6NuRVbj2ytfsztcWPrka0Y3EGP70HpxuPxYPoH07Hh4Ab84/F/aPMlcBW3x43LlZedTsNSd3e+GweePoD8p/Kr/xkQMwDJfZOR/1S+Nhs/4KebXv7147/QztXO6VQsNbTjUBz64VCtx77+4WvERcU5lJH9MvMz0SaiTfUNEIHuwpULCA6qvR0ICQqB2+N2KCNnRIRGoJ2rHc5dPIdNhzchqYd9PxBgN6/+2nfWz2YhJTsFA2IG4Lb2tyF9RzrKr5RjcqL61xYCQVlFWa3/+z967ijyz+SjRXgLxEbFOpiZtaZ9MA2rD6xGziM5cIW5cKbsDAAgKiwK4Y0Du9XLnC1zMLrbaMRGxaL0cilWH1iN3GO52PTYJqdTs5QrzIXebXrXeiyicQRahre87vFA89uPfotx3cchrnkcTpWewtzcuQgJDsHE3hOdTs1SM382E0PeHIKXP3kZE+InYOfJnXj9i9fx+tjXnU7NFm6PG5n5mUhJSNGitQ8AjOs+DvM/mY/YqFjEt4nH3tN78cqOVzAlcYrTqdli0+FN8MCDHi174PCPh/HM5mfQs1XPgN7LeDWzH+79ML678B1eyH0BZ8rOIPGmRGxM3oi2zdr6Kj+/tPvUbozIGlH951kfzQIApCSkYMX4FQ5lZb2M3RkAgOFZw2s9npmUGfBfij5bfhaPb3gcp8tOIyosCn3b9sWmxzZhVNdRTqdGFjlRcgIT10/EDxd/QOumrXF77O3Y8csd17UDCTQD2w/Ehoc3YM7WOfh93u/ROboz0u9NR3LfZKdTs8WWI1twvPg4pvTTY+MDAH8e/Wc8//HzmPrBVJwtP4sYVwyevPVJvDDsBadTs0Xx5WLM2ToHJ0pOoEV4CzzY60HMv2s+Goc0djo1y3j9vzXTb5uO6bdN90UuDcbwTsPhmatH5/OadKy5yvKk5U6n4DdyJ+U6nYIt1v7HWqdTcMzY7mMxtvtYp9NwxD1d79FurXOFuZB+XzrS70t3OhVHTIifgAnxgX9nc0112vxV/cRLSUlJvV/g4sWLypjbrf4+wZUrV5Qxs7nU5XjX/pyNN7VLjOqTVFRUKGP1zdPuusvKypQxb87J5cvq796parCi9kuXLilj0nw30pDHvLS01PRzy8vLlTEzeVpRuzT3vOHvYy49RzonRj8ZJq0D0vph53VeWVmpjF24cEEZ8/W1JVHVXfMxM/mYXae9GXcpz+Dg629dsPs6v3r1qjImzRXA3JyWSONei6cOioqKPAC0+KeoqEjL2nWtW+fada1b59p1rVvn2q+tW+fadalbNe41BXk8xr/c7Ha7cerUKbhcroDtdO7xeFBaWoqYmJha/ycR6LXrWjegb+261g3oW7uudQP61q6qG9C39kCvG5DHvaY6bf6IiIiIKDCY7vNHRERERA0PN39EREREGqnT3b46/z15oNeua92AvrXrWjegb+261g3oWzu/86ffmAN1/84f7/Y1uENGl9p1rVvn2nWtW+fada1b59p5t69+davGvaY6ffLncrkAAEVFRYiMjKzLU6qdP39eGVuwYIEytnr1avG4t99+uzK2Zs0aw7yuVVJSgo4dO1bXWsWb2s3q3Vv+2ayoqChl7P3331fGmjdvft1jVtQt5fDaa68pY0ZjfqP8vWG29sLCQuUx//KXvyhjUn3SmALAmDHq3xhNTlb/8kLfvn2ve8zuuS5d59L5AoADBw4oY2bmg9nazc7p4uJiZaygoMAoXaX9+/crY3Fxcdc9xjH3be3S+1pGRoYyZlS7dJ0vXbrUMK+aVHUD3tX+1FNPKWM3Wm+qvPXWW+Jxpff0RYsWGSdWgxVjLuUvzXdpPgDAHXfcUa88jEjjXlOdNn9VH49GRkbW+4RJjW3DwsIMX1OlcWP1z654s4hd+7re1G6W+FEtgJCQEGVMylGK+bLupk2bKmONGqmnnNHrWHX+61u7dFGZndNGYy4dt1mzZsqYXWMu8eY6NzufjdS3drNzWrpWvSHNQY553V7XH9/XQkNDlTGztd/oNb2pXcqxSZMmypjRtSCdN1/V7k3d4eHq36+X1u+IiAjxuHa9r12LN3wQERERaYSbPyIiIiKNcPNHREREpBFu/oiIiIg0UqcbPrwxadIkZSwnJ0cZmzt3rnjcFStWmIpJ+dhJql26m9QoLt2F5uu7ZVVSUlJM5SCNGwCkpqaaS8jHjh07pozl5uYqY1L+0rgBwJIlS5Qx6ZwmJiaKx/UVKX9pXDt16mTJa/p6rmdmZipjeXl5yph0F7fRGjd8+HBlzJvzZgfpOjAaG7vWKSP5+fnKmPQ+Iq0PRrVJ581fSDVI58yodmmdkNZOu66F7OxsZUx6TzZ6X5Oucyvxkz8iIiIijXDzR0RERKQRbv6IiIiINMLNHxEREZFGuPkjIiIi0gg3f0REREQa8UmrF+nWdqmlidQSZN68eeJrSm0epNvN/cWMGTNMP3fYsGHKmD+0gJBykFoZjB8/Xjyuv7R6kW7Nl+aedMu/0XyXWoYYnTc7mG1jI7VPAOS5JI2D0XHrS2qZI4259Dyj+ewvLU9UpLql9jeLFy+2IBvfk9p3mJ0PRq3GpPdSfyGtN+np6cqY0XuTNN/94X3N7JhnZWWJx5XWfivr5id/RERERBrh5o+IiIhII9z8EREREWmEmz8iIiIijXDzR0RERKQRbv6IiIiINOKTVi9mWxIY3fZuxWv6mtTGQmrlILURaAiklgTSLfHSuDWENgfe8Kb9iNRKwK42CFIbB6mdgdTawyj34uJiZUyaZ3aSrmWz7UIA/78ezLbU8ofWRHWRlJSkjMXFxSljUnszozVAOjfSfLCzFYo0b822dgPkVlj+QHo/l1qYGY2NdFxft6yqiZ/8EREREWmEmz8iIiIijXDzR0RERKQRbv6IiIiINMLNHxEREZFGuPkjIiIi0ohPWr2YveU/EEi330sxqVWAURsYf2hxId2+Pm/ePFPHNKpbaqvjL61/JFKrFKMxdaodQE1mW49ILRykc2KkX79+pp9bX9L5N9tmY/LkyeaS8RPS9Sjp3LmzGE9ISFDG0tLSlDGpNYuvWTX3pJZJ0vUntRrxNakdjTR2Rq3d/H0Nl/Lz5vxL51PaW3m7D+Anf0REREQa4eaPiIiISCPc/BERERFphJs/IiIiIo1w80dERESkEW7+iIiIiDTCzR8RERGRRnzS589sv5ni4mJlzKiHlNT/xmyfOTOk2qXePzk5OcqY1PcHsK5vmq9Ifc+k3KOiosTj+nsfKCPSeTHqlWl2ng0fPlw8bn1I15V0vUp9CKU1AJD7YdrZ102ae1L/Muk6N2Jljy9fMLvOzpgxw/RrSs/19XyQ5vTcuXOVMel6NOqVKc0lo/cFfyDVbpS/nb0K/YnU71O6xrzt78pP/oiIiIg0ws0fERERkUa4+SMiIiLSCDd/RERERBrh5o+IiIhII9z8EREREWnEJ61epDYIw4YNU8YWL16sjG3YsMH0a/pDGwQjRm1NJP7e8iQ1NVUZW7JkiTJmdE6k45ppxVFaWiq+norUAiIvL08ZO3funDJm1KJHaoli1D7CV6RzLLXwkc5XdHS0+Jq+bFXjDbNjnpKSoowlJCSIr+nv65g3bT0kZtcP1XVg9jqX5rvUgkNq12LUwszONmUSKU+pZZX0PLvWKatItRm16pIcPXpUGZNaRXk7373+5O+1na+hU3onNHmpCQb9v0HYeXKnt4f0e9sKt2HcmnGI+VMMgtKCkH0w2+mUbLHgkwUY+MZAuBa40OaPbTB+7Xgc+v6Q02nZImNXBvpm9EXkgkjEZsTinr/eg83HNjudlu0Wbl+IoLQgpG5MdToVy83LnYegtCAEpQUhekk0opdE47b/uc3ptGxxsuQkHnvnMbT8Q0uEzw9Hn4w+2H1qt9NpWa5TeqfqMa/5z7T3pzmdmqUq3ZV4/h/Po/OSzgifH45+K/rhj//7R3g8HqdTs0Xp5VKkbkxFXHocwueHY8jyIdh1cpfTaVnKq0/+/lrwV8z6aBaWjlmKQR0GIX1HOu5ddS8OTT+ENhFtfJWj3ymvKEdC2wRMSZyCn6/7udPp2CavMA/TBk7DwJiBuOq+iuf+8RzuWXUPvpz6JSJCI5xOz1IdIjtg4ciF6NaiG4pLirHmqzVI/nsy8h7NQ6+WvZxOzxa7Tu7Csj3L0LdtX6dTsU1863hseXxL9SevjYJ98pclfu3cxXMY+uZQjOg8Ah8mf4jWTVvjmx+/QXQT+VPaQLDriV2o9FRW/7ngbAFGrRyFh+IfcjAr6y36dBEydmcga3wW4tvEI++bPEzfPB2RYZF4MvFJp9Oz3K/+/isUnC3AygdWIsYVg1X7V2HkypH4cuqXaB/Z3un0LOHVSvbKjlfwRP8nMLnfTx2ql45dive/eR9v7n0Ts2+f7ZME/dHobqMxuttop9Ow3cbHNtb684qkFWjzX22w5/Qe3Bl3p0NZ2WNcj3HV/34+5DyeH/I83tz/Jnaf3q3F5q+sogzJ7yTjjXFv4KVtLzmdjm0aBTfCTc1uQpOrTZxOxTaLPl2EjlEdkZmUWf1Y5+jODmZkn9YRrWv9eeH2hega3RXD4tRfXwoEnxV9hqQeSRjTfQwAoHm35lh/aD32nNnjcGbWu3jlItZ/uR45j+RUv4/NGz4Pf//678jYnYGX7grM9c70X/tWVFZgz6k9GNll5L8PFhSMkV1G4vMTn/skOfJvxZd/+jSkRXgLhzOxV6W7EusPrceFqxcwsN1Ap9OxxbQPpmFMtzG1rncdfPPjN4j5UwwSMxPxxMYnUFRS5HRKlnv30LsY0G4AHvrbQ2jzxzbot6wf3tjzhtNp2a6isgKr9q/ClH5TEBQU5HQ6lhrScQi2Ht2Kr3/4GgBw4LsD2HFqB0Z2Cvzr/ar7Kio9lWjSqPb/4IU3Csf249sdysp6pj/5+/7C96j0VKJtRNtaj7eNaIuD3x/0OjHyb26PG6kbUzG041D0btPb6XRsceDbAxi8fDAuXb2EiMYRWDlmJXq27Ol0WpZbW7AWX5z+ArueCOzvwFxrUPtBWJG0Aj1a9cA3Z77Bov9dhPvfvh+fPfYZXKEup9OzzJFzR5CxOwOzBs/Cc7c/h12nduE3G3+D0JBQpCSqb2AJNNkHs3H+0nlMSpzkdCqWm337bJRcLkHPV3siJDgEle5K/G7I7zCh5wSnU7OcK8yFwR0G48VtL6JX615oG9EWawrW4PMTn+PmFjc7nZ5lAv8LLGSJae9PQ8HZAmyfErj/Z3StHq16IP+pfJz47gRyDudg6uapeO/B9wJ6A1hUXIQZG2dg8y82X/d/xoGu5lc7YsNiMeCmAejzZh9kf52NX/T+hYOZWcvtcWNAzAC8fPfLAIB+7fqh4GwBlu5ZqtXmb/ne5RjdbTRiXDFOp2K5df9ch7cOvIXVD65GfOt4fHrkUzy37Tm0i2iHibdMdDo9y618YCWmvDsF7V9pj5CgEPRv1x8Te0/EntOB+9fepjd/rZq2QkhQCL4t/7bW49+Wf4ubmt1U/efs7GzlMaRb+o1unZZaSzQEUhsHoxYQ+/btU8ak29F91SJm+gfT8d4372HbpG3oENnhurjU6kC63d+otYU0l6TaVO1CysvLxde7VmhIKG5ucTMalTTCjPgZ2HVyF/5753/j5cEvV/83UvsibyQlJSlj0vn21p7Te3C2/Cz6L+tf/VilpxLbCrfh1Z2v4vLvLiMkOEQ8hnSdG7X3sbK2+qhaj2LCYrDj6x3oc7VPdUxq5yK16JHms5Paudrhlta31HqsV6teWP/V+lqPSderNOZG7Uykdi7SdaBqQVJSUiK+3o0Uni/EliNb8M6Ed+r9XGkN9pfWRdd6ZvMzmD10Nh7p/QgAoE/bPvj+yvdY8sUSPD3k6Vr/rdn6pHF1WtcWXZE3KQ/lFeUouVyCdq52ePjth9Elukv1fyPtOWbOnGn6taX3e2m+q97zgoPr9m0+09/5Cw0Jxa0xt2Lrka3Vj7k9bmw9shWDOww2e1jyYx6PB9M/mI4NBzfgH4//Q5svgau4PW5UVFY4nYal7u58Nw48fQD5T+VX/zMgZgCS+yYj/6l8w41fILlYeRGnLp5Ci9DA/o7r0I5DceiH2i2cvv7ha8RFxTmUkf0y8zPRJqJN9Q0Qge7ClQsIDqq9HQgJCoHb43YoI2dEhEagnasdzl08h02HNyGph3rz1dB59de+s342CynZKRgQMwC3tb8N6TvSUX6lHJMTJ/sqP79UVlGGwz8erv7z0XNHkX8mHy3CWyA2KtbBzKw17YNpWH1gNXIeyYErzIUzZWcAAFFhUQhvHO5wdtaas2UORncbjdioWBw8dxDvHnkXO87sQNaoLKdTs5QrzHXddzojGkegZXjLgP+u528/+i3GdR+HuOZxKCguwIpjKxAcFIy729ztdGqWmvmzmRjy5hC8/MnLmBA/ATtP7sTrX7yO18e+7nRqtnB73MjMz0RKQooWrX0AYFz3cZj/yXzERsUivk089p7ei1d2vIIpiVOcTs0Wmw5vggce9GjZA4d/PIxnNj+Dnq16BvRexquZ/XDvh/Hdhe/wQu4LOFN2Bok3JWJj8ka0bdbW+MkN2O5TuzEia0T1n2d9NAsAkJKQghXjVziUlfUydmcAAIZnDa/1eGZSZsB/Kfps+Vk8vuFxnC47DVdjF3pG90TWqCzcEXOH06mRRU6UnMDE9RPxw8UfEBkSiT5RffBav9fQPLS506lZamD7gdjw8AbM2ToHv8/7PTpHd0b6velI7pvsdGq22HJkC44XH8eUfnpsfADgz6P/jOc/fh5TP5iKs+VnEeOKwZO3PokXhr3gdGq2KL5cjDlb5+BEyQm0CG+BB3s9iPl3zUfjkMZOp2YZr/+3Zvpt0zH9tum+yKXBGN5pODxz9eh8XpOONVdZnrS8+t8b+s8UeSt3Uq7TKdhi7X+srf536afMAtHY7mMxtvtYp9NwxD1d79FurXOFuZB+XzrS70t3OhVHTIifgAnxgX9nc01e/7wbERERETUcdfrkr+r3/czcNSU9p6JC/WX5yspKZQwAysrKTL2m0XOu/S1Db2qvy+vdiFHtZo97o7uArKhbGpsrV64oY5cvXxaPK52Xq1evKmOqu3ovXLgAoP61Sz+cLeUhMRpz6bzVd4zsnuvSdW7026HSHdl2XudSHmZ//9ToB9h9OQ52j/mlS5eUMW9+L9bMdWB37d6scXaMec3HzLyeVJ/brb5BpGq9VfH3+S7NaW9Ia7+Z+V61rhheZ546KCoq8gDQ4p+ioiIta9e1bp1r17VunWvXtW6da7+2bp1r16Vu1bjXFOTxGP9vmNvtxqlTp+ByuQL2Z248Hg9KS0sRExNT6xOyQK9d17oBfWvXtW5A39p1rRvQt3ZV3YC+tQd63YA87jXVafNHRERERIGBN3wQERERaaRON3zo/FFpoNeua92AvrXrWjegb+261g3oWzv/2le/MQfq/te+vOHD4EuSutSua906165r3TrXrmvdOtfOGz70q1s17jXV6ZM/l8sFACgqKkJkZGRdnlJt//79ytjTTz+tjMXGyj+Tdscd6l9WmDp1qnFi1ygpKUHHjh2ra63iTe2SwsJCZaxv376mjyud77i4uOses6LuBQsWKGMLFy5UxlavXi0ed8wY3/7Optnaz507pzxmenq6Mvbxxx8rY/v27RNzjYqKUsaystQ/MTdixIjrHrN7rkvuv/9+MZ6RkaGM3Wg+G7GidqkGaZ0yIo15fdc4K+o+f/68MiZdq8XFxeJxpXXAzNpo93yX1r+33nrL9HHff/99Zaw+azvgXe1PPfWUMiaNrdGc9eZauZYVY/7ss88qY9u3b1fGkpPlX8Yxs1+RSONeU502f1Ufj0ZGRtb7hDVr1kwZCwlR/yh848byz6o0adJEGfPmQr72o2BvapcYDYwVx5Xy92XdYWFh9frvqzRt2lSMW7UhqW/tUl8mqXZpvhuR/ooiIiJCGbNrzM1q1EhegszOZyO+rF2qwey1AFizxvmybqmnmzTXxb+Kgvye4S9jLpHG3Kh2ia/W9pqPmak9NDRUGZPet6V1qioXX7PrfU2a79J1XJWLFYz+Wps3fBARERFphJs/IiIiIo1w80dERESkEW7+iIiIiDRSpxs+vDFv3jxlTLrD0ejux5ycHGVs/PjxylinTp3E49rl2LFjTqfgFelOv+zsbGUsKSlJGZPGDYBXPwjvS0eOHFHG9uzZo4yNGjXKVAwANm/erIxJd6FJ+dhlxYoVypjRddC8eXOf5mJWfn6+MpaXl2cqJl0LADB8+HCjtBwl3dkurd8JCQnicf1lzM2S3mOMxlRaO1NTU009z065ubnKmDfvedJx7Zov0hogzfeZM2eKx3Vqv8JP/oiIiIg0ws0fERERkUa4+SMiIiLSCDd/RERERBrh5o+IiIhII9z8EREREWnEJ61epNuwpZYsM2bMUMakFjEAkJiYaJCVPaSWJ9Kt4Ub1SYYNG6aM2dXKRrq9Xhobqe2H0ZhK59PO+XDrrbcqY1JLFonUPgYA1q1bp4w9+eSTpl7Tl6Q1YPLkycrY4sWLxeNK7US8uYbqS5rvcXFxypg0ZxtCSxOpPUdaWpqpY0prAOA/7bjMmjRpkqkYINfuL/PFbCsbo3Y00nGl68gfWiJJ7YuM2tZJa6fRfPEGP/kjIiIi0gg3f0REREQa4eaPiIiISCPc/BERERFphJs/IiIiIo1w80dERESkEZ+0ejFLauNgpLCw0HeJeEFqWzBz5kz7EvEjqampypjUGsfolviG3gJCaufStWtX8bn9+/dXxn7961+bzslXpDGXWjpJzwOAoKAgZUyaD75ukWA0N1Xy8vKUsaSkJLPp2Ea6XiX+0I7KW1KbG2ndl9qSGJ1P6X3NX86b1GJJarll1KrGbAsZu0hritTOyoh0PtnqhYiIiIh8gps/IiIiIo1w80dERESkEW7+iIiIiDTCzR8RERGRRrj5IyIiItKIT1q9mL0NW7rt3ei2cKmVgHQbvnRbtRlSqwrpvEhtbrKyssTXlFoQ+APpdn/pfEljChjPCX/XpUsXZaxz587ic2fPnq2MRUdHm86pPqTrSmqFIs2H8ePHm87HyjYI10pISFDGpHVMqk9qgQN41wrLV8y21JLWKKn9DeA/LXCk+Z6WlmZfIv9/dq5/0pyWrjuzLZEAuUWOP5DqlmJG79fS2i+dE2ldrQt+8kdERESkEW7+iIiIiDTCzR8RERGRRrj5IyIiItIIN39EREREGuHmj4iIiEgj3PwRERERacQnff4kUVFRypjUc8+ox5XUh6hTp05yUjaR+vB4k6O/1Kci9SaSemcZ9TcMZKNGjRLjzz77rDL20EMP+TqdG5J6WUm9Bjds2KCM+XvPyirSNSetRVJ9Rr0dpZ6Ydq0BcXFxpp4n9Qf0prdjZmamMubrvo/S+5PZfrFGtefm5ipjdva1lEg57t27VxmT1n5Ars/ouf7M6FqV+n1K+yBvzwk/+SMiIiLSCDd/RERERBrh5o+IiIhII9z8EREREWmEmz8iIiIijXDzR0RERKQRy1u9SLdvZ2dnmz6u1F7Bm1YCdvGmVUNeXp4yJrWWsKs9hNnzL7UJMIpLrym13PG1RYsWKWPnzp1TxtatWyceV5rv/iApKclUzKhdweTJk82mZBup9YUUM+IP17L0OlIbGKnVizek+eIvrVCkFj05OTnicxcvXqyMNW/e3GRG9Se9lhQz2+YL8P/3bak26To32udI17l0HanaDZWWloqvV8XrT/5e2/kaOqV3QpOXmmDQ/xuEnSd3entIv7etcBvGrRmHmD/FICgtCNkHs51OyRYLPlmAgW8MhGuBC23+2Abj147Hoe8POZ2WLTJ2ZaBvRl9ELohE5IJIDF4+GB9+86HTadlu4faFCEoLQurGVKdTsdy83HkISguq9U/PV3s6nZYtTpacxGPvPIYuy7qg3avtMGTVEOz9Vv6fs0DQKb3TdWMelBaEae9Pczo1S1W6K/H8P55H5yWdET4/HF3/uytezHsRHo/H6dRsUXq5FKkbUxGXHofw+eEYsnwIdp3c5XRalvLqk7+/FvwVsz6ahaVjlmJQh0FI35GOe1fdi0PTD6FNRBtf5eh3yivKkdA2AVMSp+Dn637udDq2ySvMw7SB0zAwZiCuuq/iuX88h3tW3YMvp36JiNAIp9OzVIfIDlg4ciG6tegGDzzIys9C0tok7H1yL+LbxDudni12ndyFZXuWoW/bvk6nYpv41vHY8viW6j83Crb8L0scd+7iOQx9cyhGdB6BvyX9Da3CW+Ff5/+F5mHNnU7Ncrue2IVKT2X1nwvOFmDUylF4KN6eRupOWfTpImTszkDW+CzEt4nH7lO7MTlnMqKaROE3g37jdHqW+9Xff4WCswVY+cBKxLhisGr/KoxcORJfTv0S7SPbO52eJbxayV7Z8Qqe6P8EJvf76a9mlo5dive/eR9v7n0Ts2+f7ZME/dHobqMxuttop9Ow3cbHNtb684qkFWjzX22w5/Qe3Bl3p0NZ2WNcj3G1/jz/7vnI2J2BHSd2aLH5K6soQ/I7yXhj3Bt4adtLTqdjm0bBjXBTs5ucTsNWiz5dhI5RHZGZlFn9dYO4KHO/9NHQtI5oXevPC7cvRNforhgWN8yhjOzxWdFnSOqRhDHdxwAAOjXvhDUFa7T4m7yLVy5i/ZfrkfNITvX72Lzh8/D3r/+OjN0ZeOmuwFzvTP+1b0VlBfac2oORXUb++2BBwRjZZSQ+P/G5T5Ij/1Z8uRgA0CK8hcOZ2KvSXYm1BWtRfqUcgzsOdjodW0z7YBrGdBtT63rXwTc/foOYP8Wgy5IuSH4nGceLjzudkuXePfQuBrQbgIf+9hC6vd4Nd66+E1kF+v30YkVlBVbtX4Up/aYgKCjI6XQsNaTjEGw9uhVf//A1AGDfmX3Yfnw7Rt8c+B9yXHVfRaWnEk0aNan1eHijcGw/vt2hrKxn+pO/7y98j0pPJdpGtK31eNuItjj4/UGvEyP/5va4kboxFUM7DkXvNr2dTscWB749gMHLB+PS1UtoFtoMGx7egFta3+J0WpZbW7AWX5z+ArueCOzvwFxrUPtBWJG0Aj1a9cDp0tNIy0vDHZl3oODpArjCXE6nZ5kj544gY3cGZg2ehf+b8H/xxbdfYHbubIQGh2LiLROdTs822Qezcf7SeUxKnOR0KpabfftslFwuQc9XeyIkOASV7krMv2s+kvsmO52a5VxhLgzuMBgvbnsRvVr3QtuItlhTsAafn/gcN7e42en0LBP4X2AhS0x7fxoKzhZg+5TA/T+ja/Vo1QP5T+Wj+FIx3v7ybaRkpyBvUl5AbwCLioswY+MMbP7F5uv+zzjQ1fxqR9+2fTGowyDEpcdh3T/X4Zf9f+lgZtZye9wYEDMAL9/9Ms6fP4++bfriqx++QuaBTK02f8v3LsfobqMR44pxOhXLrfvnOrx14C2sfnA14lvHI/9MPlI3pSLGFYOUxBSn07PcygdWYsq7U9D+lfYICQpB/3b9MbH3ROw5vcfp1CxjevPXqmkrhASF4Nvyb2s9/m35t7W+IyPd9m721mlAvm3czlvizRo+fLgyNmyY/P0S6bzZ0R5i+gfT8d4372HbpG3oENnhurg05tJt7960xTBz3JKSknq9RmhIaPX/Cd4acyt2ndqFJTuWYNm4ZdX/zcKFC5XPl9q1jBwp/3XqsmXLxLhV9pzeg7PlZ9F/Wf/qxyo9ldhWuA2v7nwVl393GSHBIaaPb9T+Ye7cuaaP7WvNmzRH95bdcfjHw7UeT09PVz5HulZnzJghvp60Rlipnatd9f/QVK2lie0T8d6R92qtrdI1Z3bdr/maN2JXO5DC84XYcmQL3pnwTr2fK9WXkJAgPtepdjXPbH4Gs4fOxiO9HwEA9GnbB4XFhViwfcF1mz8pR1X7EaOY0XGt1rVFV+RNykN5RTlKLpegnasdHn77YXSJ7lL933jTzkUivS9LbcpUz6vr+5rp7/yFhoTi1phbsfXI1urH3B43th7ZisEd9PgelG48Hg+mfzAdGw5uwD8e/wc6R3d2OiVHuT1uXK687HQalrq789048PQB5D+VX/3PgJgBSO6bjPyn8r3a+DU0ZRVl+NeP/0I7VzunU7HU0I5DceiH2i2cvv7ha21u+gCAzPxMtIloU30DRKC7cOUCgoNqbwdCgkLg9rgdysgZEaERaOdqh3MXz2HT4U1I6qHuUdrQefXXvrN+Ngsp2SkYEDMAt7W/Dek70lF+pRyTE/2/Mas3yirKav3f/9FzR5F/Jh8twlsgNirWwcysNe2DaVh9YDVyHsmBK8yFM2VnAABRYVEIbxzucHbWmrNlDkZ3G43YqFiUXi7F6gOrkXssF5se2+R0apZyhbmu+05nROMItAxvGfDf9fztR7/FuO7jENc8DqdKT2Fu7lyEBIdgYu/A/qvPmT+biSFvDsHLn7yMCfETsPPkTrz+xet4fezrTqdmC7fHjcz8TKQkpGjR2gcAxnUfh/mfzEdsVCzi28Rj7+m9eGXHK5iSOMXp1Gyx6fAmeOBBj5Y9cPjHw3hm8zPo2apnQO9lvJrZD/d+GN9d+A4v5L6AM2VnkHhTIjYmb0TbZm2Nn9yA7T61GyOyRlT/edZHswAAKQkpWDF+hUNZWS9jdwYAYHjW8FqPZyZlBvyXos+Wn8XjGx7H6bLTiAqLQt+2fbHpsU0Y1XWU06mRRU6UnMDE9RPxw8Uf0Lppa9weezt2/HLHde1AAs3A9gOx4eENmLN1Dn6f93t0ju6M9HvTtfjyPwBsObIFx4uPY0o/PTY+APDn0X/G8x8/j6kfTMXZ8rOIccXgyVufxAvDXnA6NVsUXy7GnK1zcKLkBFqEt8CDvR7E/Lvmo3FIY6dTs4zX/1sz/bbpmH7bdF/k0mAM7zQcnrl6dD6vSceaqyxPWu50Cn4jd1Ku0ynYYu1/rHU6BceM7T4WY7uPdToNR9zT9R7t1jpXmAvp96Uj/b50p1NxxIT4CZgQP8HpNGzl9c+7EREREVHDUadP/qp+36++d0cC8o8MX716VRmrrKxUxgCgvLxcGTOTZ9Vzrv0tQ29ql5g9LzVzupH6nhcr6r506ZIyZlSbWdJ8UdVQNQa+rN3sb2EanRdpvtQ3T7vnusSo7suX1TfU+Mt1fuXKFWXM7VZ/YV6qzWwuRsfyZd1lZWXKmDSuRteIdM6ktUVVg93z3Zv3NSmX4OD6fVajqrvmY2Zql+at2bEzysVXtTe09zVpbanvfL+Opw6Kioo8ALT4p6ioSMvada1b59p1rVvn2nWtW+far61b59p1qVs17jUFeTzGH1W43W6cOnUKLpcrYH/mxuPxoLS0FDExMbX+LyPQa9e1bkDf2nWtG9C3dl3rBvStXVU3oG/tgV43II97TXXa/BERERFRYOANH0REREQaqdMNHzp/VBrotetaN6Bv7brWDehbu651A/rWzr/21W/Mgbr/tS9v+DD4kqQutetat86161q3zrXrWrfOtfOGD/3qVo17TXX65M/lcgEAioqKEBkZWZenVHvqqaeUse3btytjffr0EY87Z84cZaxv377GiV2jpKQEHTt2rK61ije1FxYWKmOPPvqoMjZ2rNxcVaq9vszWbba2goICk5nK7r//fmVszZo1N3zcbO1vvfWW8rX+8pe/KGPPPfecMrZ//35lzMjTTz+tjDVv3vy6x6yY65L3339fGXv22WdNPzcuLq7euZitXRqfMWPUv/86derUeudYJTZW/VORycn1+7UNK8Zcug4WLFigjN1+++3icaX1zc4xlwwdOlQZk967Fi5cKB73RterWaq6Ae9ql9Y4iTRfAPm94b333lPG7rjjjuseMzvm58+fV76ONKeXLl2qjPXuLf8MpnQtm1k/pHGvqU6bv6qPRyMjI+s9UUJDQ5Ux6SPJxo3ln1Vp1qyZMubNG9e1HwV7U7t08kNCQpSxsLAw8bi+fGOuUt+6zdZmFWm+GJ2v+tYeHq7+HWOp9qZNmypjRmMukeqTYr6c6xKpbqP+XdI8s/M6l9Yb6a+PvBlXaZ6Zrd2XYy7lJ42r9J4A+M+YS6TrXKrP6HXsWNtrPmam9iZNmpjKw5v3hYiICGXMl2uc1KfQ7LVsVLd0Pn0536/FGz6IiIiINMLNHxEREZFGuPkjIiIi0gg3f0REREQaqdMNH0Zyc3OVsaysLGUsISFBGRs/frz4mlI8Pz9fGfPl3VRGpPOyb98+UzEA6NSpkzI2adIkg6x8w2z+KSkpytgDDzwgvmZUVJQylpiYKD7Xl44dO6aMSbUbzWmz/GE+SHfJzZ07VxkzGjepNjtJ9RUXFytjaWlppl9TWh+HDx+ujNl1zlJTU009T1qfAXlOSGuqr9eAnJwcZUy6zqW5smLFCvE1zZ5TOxnVoGJUm3Rcac5I10J9STlkZ2crYx9//LGpYxod18r5wE/+iIiIiDTCzR8RERGRRrj5IyIiItIIN39EREREGuHmj4iIiEgj3PwRERERacQnrV7Mkm5xNmpXID1XurXazlvpo6OjlTGpbYk3tdvV2uPcuXOmnie1YzD60XY727lIzLbSmDFjhjLmTcsTX7Y6MCsvL08Zk9piSHPZn5htESWNudFa5A9tbqS2RlKLG6mlk1HrC+lakJ6bnp4uHre+pDVaIq3BRjk2hFYv0vhItRuNu3SN2fW+JuUgtfCR1jGp3R0AJCUlGWRlDX7yR0RERKQRbv6IiIiINMLNHxEREZFGuPkjIiIi0gg3f0REREQa4eaPiIiISCM+afWSm5tr6nnetDKQbsnu3Lmz6eP6knQL97x585SxmTNniseV2i/YJT8/39TzjGqTZGZmKmN2tQLwxpIlS5Qxo7YSRu0CnCa1/pFqk9rAAP7R7gQw3+pFGnOj1hfSumpX2yOzdT/wwAOWvOaIESNMH7e+pLkntaVKS0sz/ZrSnPCXNU46L9L4SO1/AP9o+ySdY+k9T3pPXrx4sfiavm5RVFf85I+IiIhII9z8EREREWmEmz8iIiIijXDzR0RERKQRbv6IiIiINMLNHxEREZFGfNLqxQlSGwR/uSVekpqaaioGyLfaS7ej+7I9hHSOpVYNw4cPV8aMbnmXzoudYy69ljQ2xcXFyphRGwSpXYDUUsiXzp8/r4xJY+NN3dJ8kdpimG1RoiKNqzQ2Uh5GrV6kuF3tIcyeR6kVihFpnkkthXzN7DorxYzamUjjOn78eGXM1/NdqsFo3vr6ef7CqmtOavsmtZDxtg0WP/kjIiIi0gg3f0REREQa4eaPiIiISCPc/BERERFphJs/IiIiIo1w80dERESkEW7+iIiIiDTit33+pF5PAFBYWKiM+bKfnT+SeqpJPYOMekzVh3SOpZg0rkZj3hBIfemk3llSLzzAP+a0ND5SzynpedI5AeTeZtJct6sPHiBfj1LtUv6A9328fEHKPyoqShmT1mejMZdI88FOZnuZSjFAvs6l9dvXfU7NvpY0tjk5OeJr2tWv1N9Ic8LKfsb85I+IiIhII9z8EREREWmEmz8iIiIijXDzR0RERKQRbv6IiIiINMLNHxEREZFGfNLqRbpVOS0tTRmT2ggY3cYstRmQbsP3F9It8UYtT6R2ADNnzlTGjh07dt1jpaWl4muZId2eLrXF2Ldvn3jczMxMkxn5ljQ+UosRqX2CNJ8B37dyMENqPSLVPWLECGVsxYoV4ms2hPY/UguLGTNmKGNGtRm1grGDtJZK7Ymka9Wo1Yv0fuIva7s05nv37lXG+vXrJx5Xql2aD75eH6Q8pGtWWiOk8wL4R6sXaW5K51hqQWQ05tJrTp48WXyuN7z+5O+1na/hkR2P4J5t9+DpL57GVyVf+SIvv1Z6uRSpG1MRlx6H8PnhGLJ8CHad3OV0WpablzsPQWlBtf7p+WpPp9OyRc3ao5dEI3pJNG77n9ucTssWJ0tO4rF3HkPLP7RE+Pxw9Mnog92ndjudluV0nu/AT2t7p/ROaPJSEwz6f4Ow8+ROp1OyhY7re6W7Es//43l0XtIZ4fPDkfy/yfifwv+Bx+NxOjVbVI356I9G42d//xlStqXgn+f+6XRalvLqk7+/FvwVsz6ahdSbU9HL1Qtvn3wb/3ngP/E/A/8H0aHRvsrR7/zq779CwdkCrHxgJWJcMVi1fxVGrhyJL6d+ifaR7Z1Oz1LxreOx5fEt1X9uFOy3fcJ9rqr2qk88dKj93MVzGPrmUIzoPAIfJn+I1k1b45sfv0F0k8C9vmvSdb5Xre1LxyzFoA6DkL4jHfeuuheHph9Cm4g2TqdnKR3X90WfLkLG7gxkjc9CfJt4ZG3OwqJDixAREoEHOzzodHqWqxrzl/q/hNZNWuODEx/gqc+ewvq71qNNeGDOd68++Xtlxyt4ov8TGH3TaHSK6IRZ3WahSXATfHjmQ1/l53cuXrmI9V+uxx9G/gF3xt2Jm1vcjHnD5+HmFjcjY3eG0+lZrlFwI9zU7Kbqf1o1beV0Srapqr1tRFu0jWiLluEtnU7Jcos+XYSOUR2RmZSJ29rfhs7RnXFP13vQtUVXp1Ozha7zvWptn9xvMm5pfQuWjl2Kpo2b4s29bzqdmqV0Xd8/K/oMST2SMKb7GHRq3gnDWg/DgOgBOFh60OnULFdzzG9tdStim8XiqZ5PoWNER/zt2N+cTs8ypjd/FZUV2HNqD0Z2GfnvgwUFo390f/yzJHA/Lr3qvopKTyWaNGpS6/HwRuHYfny7Q1nZ55sfv0HMn2LQZUkXJL+TjOPFx51OyTZVtSdmJuKJjU+gqKTI6ZQs9+6hdzGg3QA89LeH0OaPbdBvWT+8secNp9OyjY7zXbW2j+wyEp+f+NzBzKyn6/o+pOMQbD26FV//8DUA4HDZYRQUF+C2FoH/1RbVmIeFhGHvD/L3FBsy05u/7y98j0pPJdpGtK31eHTjaPxY8aPXifkrV5gLgzsMxovbXsSp0lOodFdi1f5V+PzE5zhddtrp9Cw1qP0grEhagY2PbUTGmAwcPXcUd2TegdLLvr9pxN/UrP1Pd/0JhSWFuP/t+1FaEdi1Hzl3BBm7M9CtRTdsemwTnh7wNH6z8TfIys9yOjXL6TrfVWt724i2OFN2xqGs7KHr+j779tl4pPcj6PlqTzR+sTF+vefXeLDDgxjVdpTTqVmu5pifvXgWlZ5KvF/0Pvb/uB/fX/re6fQso8cXWHxs5QMrMeXdKWj/SnuEBIWgf7v+mNh7Ivac3uN0apYa3W109b/3bdsXgzoMQlx6HNb9cx1+2f+XDmZmvZq1x4bFYsBNA9DnzT7I/jobv+j9Cwczs5bb48aAmAF4+e6XAQD92vVDwdkCLN2zFCmJKQ5nZy2d57vOdFzf1/1zHd468BZWP7ga8a3jsSZ3DV47/BpahrbEfTfd53R6lqsa83s/uhchQSHoGdUT93W4D1+dD9wbWE1v/lo1bYWQoBB8W/4txg8fX/145vlMdI/oXn2ruHT7dnS0+kvjw4YNE19faidita4tuiJvUh7KK8pRcrkE7Vzt8PDbD6NLdJda/92NWqtUkW6ll26XB+QWEQkJCeJzfaWqtk7NOmHP0T24u8Xd1TGptYfU0mTu3Lnia/pDuxPg37fmx4TFYMfXO9Dnap/qmNTaSKrdaD5L7X2s1M7VDre0vqXWY71a9cL6r9bXekyaz1KLG6lFAiCfMzvnQ9U11zWqKwpOF9S6BlNS1JtgqTWJtD4YPddKNdf2mr4t/xY3Nbup+s+LFy9WHkNqOWXU0kNqG2SHuqzvRmuVilFtUvscK9f2ZzY/g9lDf/r0DwA63tsRwdHBWHdwHWbfN7vWfyu9/2Rlqf9GwF9add2Iasx7hfeqXnvNtr+R1j+j4xrtg7xh+q99Q0NCcWvMrdh6ZGv1Y26PG1uPbMXgDoN9kpy/iwiNQDtXO5y7eA6bDm9CUg/n+xTZqfxKOQpLC9G6aWunU7HdxcqLOHXxFFqEtnA6FUsN7TgUh344VOuxr3/4GnFRcQ5l5JyyijIcLT6KmyJuMv6PGzCu7T/RaX2/cOUCgoNqbweCg4Lh9rgdysgZOo25V3/tO+tns5CSnYIBMQNwW/vbkL4jHeVXyjE50brGhP5g0+FN8MCDHi174PCPh/HM5mfQs1XPgK/7tx/9FuO6j0Nc8zjsObsHi/MXIyQoBP+n8/9xOjXL1ay9oLgAK46tQHBQMO5uc7fxkxuwmT+biSFvDsHLn7yMCfETsPPkTrz+xet4fezrTqdmuZpjfujUISzcsRAhwSF4sHvgt77QdW0H9Fzfx3Ufh/mfzEdsVCzi28Rj++Ht+MvevyD5lmSnU7OFjmPu1ebv4d4P47sL3+GF3BdwpuwMEm9KxMbkjWjbrK3xkxuw4svFmLN1Dk6UnECL8BZ4sNeDmH/XfDQOaex0apY6UXICE9dPxA8Xf0CLsBYY0GYA3rn/HbRsEvgtT2rWHhkSiT5RffBav9fQPLS506lZamD7gdjw8AbM2ToHv8/7PTpHd0b6velI7hv4bwo1x7xVeCsMihmEzRM2a9HuRde1HdBzff/z6D/j+Y+fx9QPpuJs+VncFHETJvWehP8c9J9Op2YLHcfc6xs+pt82HdNvm+6LXBqMCfETMCF+gtNp2G7tf6yt/nej7ysFmpq1O/l9UyeM7T4WY7uPdToN29Uc84bwM3O+puPaDui5vrvCXEi/Lx3p96UD0G++6zjmXv+8GxERERE1HHX65K/q9/1KSkrq/QJXrlyp93MA4OrVq2K8rKxMGTOTZ9Vzrv0tQ29qLy1V9wOTfjOxsrJSPK7brf4SrvTcG+VTdR7rW7dUm0Sq+/Lly+JzzYxBXY5X39rLy8tNvZ5UuzSfpVzMsGKuSy5cuGD6uWbPmaoGs7VL50TKUbpWjc5zcLDv/t/cijG/dOmSqVyM3hOkXMycEytqN1qjVbz5rVzpNW9Ug6rumo+Zme9m39MvXrwoxv19jZPen8y+JwNARUWFMmbmWpDGvRZPHRQVFXkAaPFPUVGRlrXrWrfOtetat86161q3zrVfW7fOtetSt2rcawryeIz/V8TtduPUqVNwuVwICgoy+s8bJI/Hg9LSUsTExNTaUQd67brWDehbu651A/rWrmvdgL61q+oG9K090OsG5HGvqU6bPyIiIiIKDLzhg4iIiEgjdbrhQ+ePSgO9dl3rBvStXde6AX1r17VuQN/a+de++o05UPe/9uUNHwZfktSldl3r1rl2XevWuXZd69a5dt7woV/dqnGvqU6f/LlcLgBAUVERIiMj6/KUahMnTlTGpB9tP378uHjcOXPmKGN33HGHcWLXKCkpQceOHatrreJN7ZJnn31WGVu9erX43AMHDihj9f0xeLvrltx///1ifNq0acrYmDFj6v16DWnM+/Tpo4x98MEH9crDirql2pYuXVqvY9WVdM5U88Gfau/du7d43KlTpypjycn1+4UVs3VLzX6lOSmNjZn12Rt2X+fSOXv66afF58bGxipjixYtqlceqroB72ovLCxUxm6//XZlTKoNADIyMpSxvn37GidWgxVjbvZaMKr7/fffV8bq+34OyONeU502f1Ufj0ZGRtb7hDVurP55lNDQUHVijeTUIiIilDFvLuRrPwr2pnZJWFhYnXO4lpSH2RztqltiNOZNmzZVxgJ9zKVz4w9jLtVmFW/mgz/UHhISIsbDw8OVMbvGXOpfJs1Zq9Znb9h1nUvnTHo/BOS55Ksxr/mYmdqlTYU0J4zme7NmzZQxf1jjzF4LRnVb8X5ulBPAGz6IiIiItMLNHxEREZFGuPkjIiIi0gg3f0REREQaqdMNH96Q7pA5duyYMjZ8+HDxuCNGjFDGzp07p4yZuXvGrNzcXGVsyZIlytiwYcPE49pZg69JY56Xl2f6uElJSaaf60vSmHfq1EkZmzdvnnjc9PR0U/n4knQtZ2dnK2MpKSnKmHROACAtLU0Z27t3rzJm53xITExUxqTzMn78ePG4kydPVsYmTZokJ+Uj0pgXFxcrY9L6bCQuLk4ZM3t92WnFihXKWE5OjvjchIQEH2fje0ZrlYrR+Ejv+dI8tIs0rtK1YJS7tLabPdd1wU/+iIiIiDTCzR8RERGRRrj5IyIiItIIN39EREREGuHmj4iIiEgj3PwRERERacTyVi9SOwPp1mmpJYgRf2mFItUutTOQzovRcaVbw6WWFL4k3druTYsKfxlXidSuwKh9kUSaE/n5+cqYL8dcOv9mr1dvWtgYtUqxizSnpesxKipKPG5WVpbJjHxHaq0ikVrteDMn/aHlByCfF2/mtDdrhC9Ja4o0LzMzM5Uxo7XfrvZFEul6lcZ8xowZylhqaqr4mtI6Jp0Tb1sb8ZM/IiIiIo1w80dERESkEW7+iIiIiDTCzR8RERGRRrj5IyIiItIIN39EREREGrG81Yt0q/LMmTOVMaNb+j/++GOTGfmWdPt3cXGxMiadF6O2GTk5OcqY1I7DqIVMfUg5SrXl5eWZfk1/afUijXl2drYyZkWrFMD7W/7rSmr/INUtPc9sKxFAbssg5WOnfv36KWNG81lqB2WX6Ohonx9TOieA3CbGTtI6JrU7kfIvLCwUX9Nf1jizLXW8WceklijStS7F6ks6/1KLIikHozGV6pbWR29b4/CTPyIiIiKNcPNHREREpBFu/oiIiIg0ws0fERERkUa4+SMiIiLSCDd/RERERBqxvNWLdBuzxOj26OHDh5s6rq+ZbSkh3RJv9pwBvr3tXSLdgi6NnXS+UlJSxNf0lzGXLFmyRBmLiopSxqS2QEakc+ptO4C6vk5aWpqpY0rnBJDbZtg1170h5W/Urkqa71L7HF+2/pHyl2JSfjNmzBBfc9iwYcqYna1QpNZYUkyqXWrTBdjXtsmItL5LLYjGjx9v+jXNtpfxpc6dOytj0nu2N/NSaiHjy/Zs1+Inf0REREQa4eaPiIiISCPc/BERERFphJs/IiIiIo1w80dERESkEW7+iIiIiDTCzR8RERGRRizv8yf1C1q8eLEyZtQ/Lz09XRnzpk9efUl5SKR+cEakPkt29YmS+sdJMamXk1GvO6l/lp2k/msej8fUMY3GTboepD5RviT11ZPGXOqdZdSrz85r2W5Ga4fUV0w639Ka60vSnJT62Rn1gpN6mwXyfADkMbeTNEbSvPXm/UfqlWdXf0epd6XUh1aal96s7Va+5/GTPyIiIiKNcPNHREREpBFu/oiIiIg0ws0fERERkUa4+SMiIiLSCDd/RERERBrxSasXs60FpBYVRq1eGkI7AOmWeOnW9bS0NPG4Ru0x/JnU6sWIv7RBMMubdgB2tXMxS7oeJVLLkoZCWv+kmFEbB+m5/jAfpDGfPHmy6eP6Q23eKCwsNP1cf1njpDGQ3ruk69moxY/0vuZNazRfkWqTzpfR2r5v3z5lLDMz0yAr80x/8lfprsTz/3genZd0xr2f3Ivk/03G/xT+j+k+Zw3Vwu0LEZQWhNSNqU6nYotthdswbs04xPwpBkFpQcg+mO10SrbolN4JQWlB1/0z7f1pTqdmKV3rBoCMXRnom9EXkQsiEbkgEoOXD8aH33zodFqWm5c777rx7vlqT6fTsoWu61uV13a+hk7pndDkpSYY9P8GYefJnU6nZBvdajf9yd+iTxchY3cGssZnofRIKQ6VHsKiQ4sQERKBBzs86Msc/dauk7uwbM8y9G3b1+lUbFNeUY6EtgmYkjgFP1/3c6fTsc2uJ3ah0lNZ/eeCswUYtXIUHop/yMGsrKdr3QDQIbIDFo5ciG4tusEDD7Lys5C0Ngl7n9yL+DbxTqdnqfjW8djy+JbqPzcKtvz3APyCrusbAPy14K+Y9dEsLB2zFIM6DEL6jnTcu+peHJp+CG0i2jidnqV0rN30J3+fFX2GpB5JGNN9DG5qchOGtR6GAdEDcLD0oC/z81tlFWVIficZb4x7A9FNop1Oxzaju43GS3e9hAd6PeB0KrZqHdEaNzW7qfqf975+D12ju2JY3DCnU7OUrnUDwLge43B/t/vRrWU3dG/ZHfPvno9moc2w48QOp1OzXKPgRrXGvVXTVk6nZAtd1zcAeGXHK3ii/xOY3G8ybml9C5aOXYqmjZvizb1vOp2a5XSs3fTmb0jHIdh6dCu+/uFrAMDhssMoKC7AbS1u81ly/mzaB9MwptsYjOwy0ulUyGYVlRVYtX8VpvSbgqCgIKfTsY2udQM/fc1lbcFalF8px+COg51Ox3Lf/PgNYv4Ugy5LuiD5nWQcLz7udEpkoYrKCuw5tafW+1lwUDBGdhmJz0987mBm1tO1dtOf5c++fTZKLpeg56s9ERwUDLfHjV92/iVGtR3ly/z80tqCtfji9BfY9cQup1MhB2QfzMb5S+cxKXGS06nYSse6D3x7AIOXD8alq5fQLLQZNjy8Abe0vsXptCw1qP0grEhagR6teuB06Wmk5aXhjsw7UPB0AVxhLqfTIwt8f+F7VHoq0Taiba3H20a0xcHvA/tv83St3fTmb90/1+GtA29h9YOrceHYBRwuP4zXDr+GlqEtcd9N9/kyR79SVFyEGRtnYPMvNqNJoyZOp0MOWL53OUZ3G40YV4zTqdhKx7p7tOqB/KfyUXypGG9/+TZSslOQNykvoDeAo7uNrv73vm37YlCHQYhLj8O6f67DL/v/0sHMiMhXTG/+ntn8DGYPnY1Hej+C8x3OAwCCo4Ox7uA6zL5vdvV/J90CLd06bXR7tNRGxUp7Tu/B2fKz6L+sf/VjlZ5KbCvchld3vorLv7uMkOAQw+N40/Jk+PDhpp/rNG/q9ocWEIXnC7HlyBa8M+Gdej9XauNg1AbBaUZ1S62ZUlJSlDGpbYQ/CA0Jxc0tbgYA3BpzK3ad2oUlO5Zg2bhl1f+NtBZJ7VyM1jipNZCd7Z6aN2mO7i274/CPh+ucQ1xcnDJm1BaoIa9vAJCQkKCMSecFcK72Vk1bISQoBN+Wf1vr8W/Lv8VNzW6q9Zg0ftKcMGrBJl1HSUlJ4nO9UdfapfyktkxG73lz585VxqxshWX6O38XrlxAcFDtp1f99W8gu7vz3Tjw9AHkP5Vf/c+AmAFI7puM/Kfy67Txo4YrMz8TbSLaYEz3MU6nYitd676W2+PG5crLTqdhq7KKMvzrx3+hnaud06mQRUJDQnFrzK3YemRr9WNujxtbj2zF4A6B/R1XXWs3/cnfuO7jMP+T+YiNikXHJh2x/+x+/GXvX5B8S7Iv8/M7rjAXerfpXeuxiMYRaBne8rrHA1FZRVmtTwCOnjuK/DP5aBHeArFRsQ5mZj23x43M/EykJKRo0/oC0LfuOVvmYHS30YiNikXp5VKsPrAaucdysemxTU6nZqnffvRbjOs+DnHN43Cq9BTm5s5FSHAIJvae6HRqltN5fZv1s1lIyU7BgJgBuK39bUjfkY7yK+WYnGi+YXdDoWPtplfyP4/+M57/+HlM/WAqzpadxU3NbsKk3pPwn4P+05f5kZ/ZfWo3RmSNqP7zrI9mAQBSElKwYvwKh7Kyx5YjW3C8+Dim9JvidCq20rXus+Vn8fiGx3G67DSiwqLQt21fbHpsE0Z1Deyb2k6UnMDE9RPxw8Uf0Lppa9weezt2/HIHWke0djo1y+m8vj3c+2F8d+E7vJD7As6UnUHiTYnYmLwRbZu1NX5yA6dj7aY3f64wF9LvS0f6felefY8rEOROynU6BdsM7zQcnrl6/YpLlXu63qNl7brWvTxpudMpOGLtf6x1OgXH6Ly+AcD026Zj+m3TnU7DEbrVbvo7f0RERETU8NTpk7+q3+stKSm5YVz1OABcuXJFGXO71TeHXL16VcypvLxcGZPyMXrOtb9NbFS7WZcvm//SeGlpqTJW3zztrrusrMz0c6Vz1hDGXLoWLl26JD7Xl7lYUXdlZaUyVlFRYZiLXayo3ao1zpfz3Yq6pdok0tptNpe6HM+u61xan43O2cWLF5UxX415zcfM1C6NnzSnb5RHTXbUbtWYS+uf0Zjb9b52HU8dFBUVeQBo8U9RUZGWtetat86161q3zrXrWrfOtV9bt86161K3atxrCvJ4jLaHP+1cT506BZfLFbA/6+TxeFBaWoqYmBgEB//7b8MDvXZd6wb0rV3XugF9a9e1bkDf2lV1A/rWHuh1A/K411SnzR8RERERBQbe8EFERESkEW7+iIiIiDRSp7t9df578kCvXde6AX1r17VuQN/ada0b0Ld2fudPvzEH6v6dP97ta3CHjC6161q3zrXrWrfOtetat861825f/epWjXtNdfrkz+VyAQCKiooQGRlZl6fUyfvvv6+MPfvss+JzY2PVv7OYkZGhjMXFxd3w8ZKSEnTs2LG61ipW1b5//35lbMyYMeJzpfjChQuVsebNm1/3mBV1S7XNnj1bGfv000/r9To1/eUvf1HGkpNv/HvTVtT+ySefKGPbt29XxqRxA4DVq1crY0bz5Vp2z3XpF4Buv/1208eVzknfvn1v+LgVtRcWFipj0tgUFxeLx126dKmp496I3WMuuf/++8W4dF6k94wbrW+Af833BQsWiM89fvy4MrZmzZp65aGqG7Cu9qeeekoZO3DggPhcM2OrYnbMpbGT3ruk3I3WOGm/Ut+6AXnca6rT5q/q49HIyEifTpSmTZsqY+LHlQAaNVKnLhVtlP+1HwVbVXuzZs3qnMO1QkNDlTEpRynmy7ql2qRx80Z4eLgyZueYR0REKGNhYWH1OlZN0rVidl7aNdelJqdG17lEmmd2jrm03oitFgyu84Y85hKjNSAkJEQZM7u+Af4x343WgMaNGytjvhrzmo/5unbpvUka16pczMQk9R1zaeyk2qRrWRrTqlzMxIwYrS+84YOIiIhII9z8EREREWmEmz8iIiIijVjzBawa0tPTlbF58+YpY6mpqeJxV6xYoYwdO3ZMGevUqZN4XLtItY8fP158blZWljI2adIkZWz48OFyUj4ijbn0BdbFixeLx505c6Yylp2drYxJ58TXpDyWLFmijM2dO1c8bmZmpjKWlJRkmJeTpGs5MTFRfK50LUvn2ui4viRdy9LNIEZSUlKUMem8mPmSuK9J5yQvL098blRUlDImfSHfH+oG5HV237599iXiBek8S+up2ecB/jF+ZvcO0hqXn58vvqb0fp+bmys+1xv85I+IiIhII9z8EREREWmEmz8iIiIijXDzR0RERKQRbv6IiIiINMLNHxEREZFGLG/1It2+Ld0CLd0yDvhPmwezpPqkNjaAXLt0q7pdjPJXMcrdbAsZO40YMUIZk8Zcao0ByHPa31sbSbkbtXTyl2tZWquk1ktSuxYj0nGlfOxq6SS17pByNyKNuT/MZyPetLOS1jg7SWtVTk6OMjZs2DBlzOha9wfS3JNi0jkxej+UzrWVrY34yR8RERGRRrj5IyIiItIIN39EREREGuHmj4iIiEgj3PwRERERaYSbPyIiIiKNWN7qRWoHIN3GPH78ePG4DaHth0TKX2rjYMSuVgjSre2ZmZnKmHS7vFF7n8LCQmXMX9oIJCUlKWNz585VxnJzc8Xj+kMLH7OksTFqbSHVbeeYS3NPYrbtESDPCbvmg5SDN+1cJEbrgL+TzpnR+uwv65jZ+dUQ3nutIL3nGc1n6f3eyvPJT/6IiIiINMLNHxEREZFGuPkjIiIi0gg3f0REREQa4eaPiIiISCPc/BERERFpxPJWL9JtzlIbmOHDh4vHNYr7O+n2bqPb/aX2GHadl48//lgZk9rASDFvSC01jNqJ2EUamxEjRojPldrE2NXeR2phYTZm1NYoOztbGWsIbSWkeSmtf4A8rv7QDmXx4sXKmNTSyWiu+0u7E4m0jknnpaG0ejFLutbnzZsnPldaH/39/V4aN6M2Xk7hJ39EREREGuHmj4iIiEgj3PwRERERaYSbPyIiIiKNcPNHREREpBFu/oiIiIg0ws0fERERkUZ80udP6t+TlpamjCUkJChjUn8vfyL18Bk/frwyVlxcrIzNmDFDfE2j/mB2kMZcqlsa1yVLloivmZmZqYz5wzkB5PMi9XyLi4sTj9uvXz+TGfnOsWPHlDHpOpdIYwr4T3+vYcOGKWNRUVHKmNRj0qjnm9TLz64eh2Z7r3nTh1CaZ3aSxm7mzJmmjmk03xs66X3N6D1dWkP8fe2XrgWp5yVg/j3DW/zkj4iIiEgj3PwRERERaYSbPyIiIiKNcPNHREREpBFu/oiIiIg0ws0fERERkUZ80upFakMhtbDYt2+fMia1CwG8a6HgS9It3lIeUu3e3N4t3fZudMt5fUitJqRzIo2bUbsTf7il34jUrkBqdWDU3kdqJ2IX6fxLYy49z2iuS9eQ2ZgZZud7Tk6OMjZixAjxNaUxbwjXQkMnrZfS9Sq1/5o8ebL4mtIakZqaqoz5uiWSdLzFixcrY1ILHKM5K60FUjsUu66F/Px8ZUxqbWS0FmVlZSlj0vult+2e+MkfERERkUZMf/K34JMFeOfgOzj4/UGEuEPQo2kPpMSkoH2T9r7Mz+/UrDu8UTiGdByCRSMXoUerHk6nZrlO6Z1QWFx43eNTB0zFa2NecyAj+1S6KzEvdx5WHViFM2VnEOOKwaSESfjdnb9DUFCQ0+lZRuf5XuW1na/hj5/9EWfKziDhpgT8efSfcVv725xOy1LbCrfhj5/9EXtO7cHpstPY8PAGjO853um0LFdzvjfyNEJ8ZDx+3eXXiG0a63RqljtZchLPbnkWHx7+EBeuXMDNLW5GZlImBsQMcDo1S2XsykDG7gwcO38MABDfJh4v3PkCRncb7WxiFjP9yV9eYR6mDZyGHb/cgXld56ESlZj3r3m4VHnJl/n5nZp1b/7FZlxxX8E9q+5BeUW506lZbtcTu3D6/ztd/c/mX2wGADwU/5DDmVlv0aeLkLE7A6+OfhVfTfsKi0Yuwh8++wP+vPPPTqdmKZ3nOwD8teCvmPXRLMwdNhdfPPkFEtom4N5V9+Js+VmnU7NUeUU5Etom4LX7A/t/6q5Vc77/se8fcdVzFf+5/z9xsfKi06lZ6tzFcxj65lA0DmmMD5M/xJdTv8Sf7vkToptEO52a5TpEdsDCkQux59d7sPvXu3FXp7uQtDYJ/zz7T6dTs5TpT/42Prax+t8Phx/Gb2J/g5SCFPzr4r8Q3yzeJ8n5o5p1A8CKpBVo819tsOf0HtwZd6dDWdmjdUTrWn9euH0hukZ3xbA49U9fBYrPij5DUo8kjOk+BgDQqXknrClYg50ndzqcmbV0nu8A8MqOV/BE/ycwud9P39VaOnYp3v/mfby5903Mvn22w9lZZ3S30QH/yceN1Jzv3zX7DrN7zMYDnz+Ar0u/RkJz9c+RNnSLPl2EjlEdkZn0759R6xzd2cGM7DOux7haf55/93xk7M7AjhM7EN8mcPcyPvvO34XKCwCAZiHNfHXIBqH48k+/ZdgivIXDmdirorICq/avwpR+UwL6rz2rDOk4BFuPbsXXP3wNANh3Zh+2H9+O0Tfr9Qap03yvqKzAnlN7MLLLyOrHgoOCMbLLSHx+4nMHMyO7lFf+9Al3ZONIhzOx1ruH3sWAdgPw0N8eQps/tkG/Zf3wxp43nE7LdpXuSqwtWIvyK+UY3HGw0+lYyid3+7o9biw/uRy9InohLly+YzOQuD1upG5MxdCOQ9G7TW+n07FV9sFsnL90HpMSJzmdii1m3z4bJZdL0PPVnggJDkGluxLz75qP5L7JTqdmG93m+/cXvkelpxJtI9rWerxtRFsc/P6gQ1mRXdweN149/Cp6R/ZG54jA/hTsyLkjyNidgVmDZ+G525/DrlO78JuNv0FoSChSElOcTs9yB749gMHLB+PS1UtoFtoMGx7egFta3+J0Wpbyyebvo0Yf4bug77D919vRIbJDrVhSUpLyedKt3UYtIKRWMNJzfdnuZNr701BwtgDbp2y/YVy6NVxqByDd7m8Ul24r92Xty/cux+huoxHjirkuJtUmtb4wqttJ6/65Dm8deAurH1yN+NbxyD+Tj9RNqYhxxdRaHDMzM5XHkObssGHyX537cuzMkua7NO+kcTVqUSG1QzF7Hfia1I5BcuzYMUuO6w+kNhRGc11aP+z0t/K/4XTlaWz/5fXva2Zbq0jtWgC5dm9be0jcHjcGxAzAy3e/DADo164fCs4WYOmepddt/oxqUJHatRiR2qH4Qo9WPZD/VD6KLxXj7S/fRkp2CvIm5dXaAEotZaTWbUZtulJS1JtrK8fc683f9A+m471v3sO2Sduuu0ACma51A0Dh+UJsObIF70x4x+lUbPPM5mcwe+hsPNL7EQBAn7Z9UFhciAXbF2jxf8Y6zvdWTVshJCgE35Z/W+vxb8u/xU3NbnIoK7KDbvO9navddZ909WrVC+u/Wu9QRvYKDQnFzS1uBgDcGnMrdp3ahSU7lmDZuGUOZ2Yd09/583g8mP7BdGw4uAH/ePwf2nw5VNe6a8rMz0SbiDbVNz/o4MKVCwgOqn25hASFwO1xO5SRPXSe76Ehobg15lZsPbK1+jG3x42tR7ZicIfA/j6QrnSd70M7DsWhHw7VeuzrH75GXJQ+X+Oqye1x43LlZafTsJTpT/6mfTANqw+sRs4jOXCFuXCm7AwAICosCuGNw32WoL/Rte4qbo8bmfmZSElIQaNgn3xroEEY130c5n8yH7FRsYhvE4+9p/filR2vYEriFKdTs5Tu833Wz2YhJTsFA2IG4Lb2tyF9RzrKr5RjcqL8Sw0NXVlFGQ7/eLj6z0fPHUX+mXy0CG+B2KjA7Xmn63yf+bOZGPLmELz8ycuYED8BO0/uxOtfvI7Xx77udGqWm7NlDkZ3G43YqFiUXi7F6gOrkXssF5se2+R0apYy/e6dsTsDADA8a3itxzOTMgP6JgBd666y5cgWHC8+jin9AnvTc60/j/4znv/4eUz9YCrOlp9FjCsGT976JF4Y9oLTqVlK9/n+cO+H8d2F7/BC7gs4U3YGiTclYmPyRrRt1tb4yQ3Y7lO7MSLr39+3nPXRLABASkIKVoxf4VBW1tN1vg9sPxAbHt6AOVvn4Pd5v0fn6M5IvzddixvazpafxeMbHsfpstOICotC37Z9semxTRjVdZTTqVnK9ObPM9fjyzwaDF3rrnJP13u0PAeuMBfS70tH+n3pTqdiKx3H+lrTb5uO6bdNdzoNWw3vNFzLsdex5ipju4/F2O5jnU7DdsuTljudgiPqtPnzeH66IEpKSnz64hcvqrumX716VXxuZWWlMlZWVqaMqWqoeryq1ipW1V5erv6FhMuX5e8auN3q75lduqT+hZUb1WBF3VJtkgsXLohxX4+BFbVLc1piNN+lXIKD6/fVXbvnunQ86To2Is0XO6/z0tJSZezKlSvKmFHt0nVU3zztHnOJ0VyXmMnTn2o3Wtt9+b6mqrvmY76uXXr/uVEedVXfa92KMTe7VhnVXVFRoYz5cr7fKDFDRUVFHgBa/FNUVKRl7brWrXPtutatc+261q1z7dfWrXPtutStGveagjwe4+242+3GqVOn4HK5AvbXHDweD0pLSxETE1Prk5RAr13XugF9a9e1bkDf2nWtG9C3dlXdgL61B3rdgDzuNdVp80dEREREgcFnv+1LRERERP6Pmz8iIiIijdTpbl+d/5480GvXtW5A39p1rRvQt3Zd6wb0rZ3f+dNvzIG6f+ePd/sa3CGjS+261q1z7brWrXPtutatc+2821e/ulXjXlOdPvlzuVwAgKKiIkRGRtblKdWeeuopZez9999XxqKiosTjZmRkKGN33HGHcWLXKCkpQceOHatrreJN7W+99ZYy9pe//EUZKygoEI8rPTc5uX4d2a2ou3fv3spYUVGRMtaxY0fxuHPmzFHG6ls3YL72/fv3K49pZu4BxrVPnTpVGXv00UeVsebNm1/3mBVjLpGuA6kuAHjvvfeUMX+5ziXPPvusMlZcXCw+d+nSpT7Lw+66pXXfqO41a9b4LA/Amtql9y5pzI3Wdl9S1Q04M9+NLFq0yGd52P1+LsWM5ru0Bvryfe1addr8VX08GhkZWe8TFhoaanjcGzFqXBsREaGMeTOZr83Jm9rDw9W/BRkSElL/5OpwXLO1+7Lu+jYdruvzrKgbqH/tzZo1M/1aKka1N2nSRBmTapdivhxziTRuRhrCdS4JCwtTxqS1sSoXX7Orbqm2xo0bi8+1om7At7U3bdpUGZOuZatqk9zofdaJ+W7E3+e7tI41aqTeShm919v1vnYt3vBBREREpBFu/oiIiIg0ws0fERERkUbq9J0/b0yaNEkZGz58uDKWnp4uHnfEiBHK2NGjR5WxTp06icetr/z8fGVs8uTJylhcXJwyZnSzi3Tc8ePHK2M3+vK/FVJTU5Ux6XxlZWWJx5XqTkxMNBUzQ5pDM2bMMHXMFStWiPGZM2cqY1J90jXmS+fPn1fGpGvZaK77euysINW3ZMkSZWzx4sUWZGMf6TqXruXMzEwLsrGXNHbSGhwIpDVcmu9m10Y7Seuw9P4j1SadL6PjSuu3t3sZfvJHREREpBFu/oiIiIg0ws0fERERkUa4+SMiIiLSCDd/RERERBrh5o+IiIhII5a3epFuVZZugd63b594XOnWal+3c5FIrSiys7OVsaSkJGVs3rx54mumpaUpY1LLDX9o9ZKTk6OMGbV6kdg55tJ5lNp+SDGj338cNmyYMmZXOxRpbkktnaRrWbpGAPvmrDek9hAJCQnKmHTOGgJd6wbk9y6jNmUNgVSf1MomJSVFGTM6L8eOHVPG7FrfpTXOLKNWL9K1YmXd/OSPiIiISCPc/BERERFphJs/IiIiIo1w80dERESkEW7+iIiIiDTCzR8RERGRRixv9SLx5jZmu9pbeENq52IVK25V9yXptnYjc+fOVcYaQksQqZWBEamthl21S60apBY+UvsHo2tEagsitZGys52INK5S26aGMGclUv4NYX02Iq2lUmumQKhdutYLCwuVsQceeMDUMQH5WpGuMV9eR1KbstzcXGVMWp+N2ng51RqIn/wRERERaYSbPyIiIiKNcPNHREREpBFu/oiIiIg0ws0fERERkUa4+SMiIiLSiKOtXqRbtKX2EIB8a7WdbR7y8/OVMakVhdHt32ZJ58WpW8prktr7DBs2THxudna2Mibdou8vLTWkeSmNG2C+dl+SWh1IpDE3yj0rK0sZk9o/+HoNkGqXrmWpfYU0pgAwfvx4ZcyuMZfanUgxs+1vAHnsvGkPZhepdqMxl9rESO8nviaNkTTu0vu20XueN23A7CCNnTQ2RnPWznGtiZ/8EREREWmEmz8iIiIijXDzR0RERKQRbv6IiIiINMLNHxEREZFGuPkjIiIi0gg3f0REREQacbTPn8SoJ110dLQyJvXk8nVPncLCQmVM6u8j9UqSjgkASUlJypidPQ59zaj/14gRI5QxqU+eXT3RjEg9vIzGTTo3dtUnnWOptrS0NN8nA7kPnq+Z7S8nnRej+S6tgVJ/UaOekfUh9ciUasvLyzMVA+T5IvWRU52vkpIS8fVUpH59ks6dO5t6npEZM2YoY77u4SrNd6nfnZTHzJkzxdeU5q0/9GqVrjlpThtd507hJ39EREREGuHmj4iIiEgj3PwRERERaYSbPyIiIiKNcPNHREREpBFu/oiIiIg04pNWL1LbEuk2Z6l1x7lz50znI92S7etWL1LbFSkm5SGdT8D/b4nPyclRxj7++GNlTGoh4E+k8THbdiUrK8tcMpDnu9SOo77Mti6SWi9JawAgX0N2tvCRap87d64yJl2rxcXFpl/TH64VqdWO1Ppi2LBhpl9Tuk5U7ZLKy8tNvZZ07URFRZk6ptG4SfNlyZIlypivW72YJb3/GJ0zX65VVjDb7sns86zGT/6IiIiINGJ685exKwN9M/oickEkYjNicc9f78HmY5t9mZvf6pTeCUFpQdf9M+39aU6nZqmaYx65IBKDlw/Gh9986HRattB5vte0cPtCBKUFIXVjqtOp2OJkyUk89s5jaPmHlgifH44+GX2w+9Rup9OynK51A3rXXkW367z0cilSN6YiLj0O4fPDMWT5EOw6ucvptCxl+q99O0R2wMKRC9GtRTcUlxRjzVdrkPz3ZOQ9modeLXv5Mke/s+uJXaj0VFb/ueBsAUatHIWH4h9yMCvr1RxzDzzIys9C0tok7H1yL+LbxDudnqV0nu9Vdp3chWV7lqFv275Op2KLcxfPYeibQzGi8wh8mPwhWjdtjW9+/AbRTdS/LhQIdK0b0Lv2Krpd5wDwq7//CgVnC7DygZWIccVg1f5VGLlyJL6c+iXaR7Z3Oj1LmN78jesxrvrfz4ecx/NDnseb+9/E7tO7A/7NsHVE61p/Xrh9IbpGd8WwOPPfZWkIao45AMy/ez4ydmdgx4kdAb/503m+A0BZRRmS30nGG+PewEvbXnI6HVss+nQROkZ1RGZSZvVjnaOt+ekuf6Jr3YDetQN6XucXr1zE+i/XI+eRHNwZdycAYN7wefj7139Hxu4MvHRXYJ4Hn3znr9JdifWH1uPC1QsY2G6gLw7ZYFRUVmDV/lWY0m8KgoKCnE7HNpXuSqwtWIvyK+UY3HGw0+nYSsf5Pu2DaRjTbQxGdhnpdCq2effQuxjQbgAe+ttDaPPHNui3rB/e2POG02lZTte6Ab1rB/S8zq+6r6LSU4kmjZrUejy8UTi2H9/uUFbW8+pu3wPfHsDg5YNx6eolRDSOwMoxK9GzZU9f5dYgZB/MxvlL5zEpcZLTqdii5pg3C22GDQ9vwC2tb3E6LVvoOt/XFqzFF6e/wK4nAvs7MNc6cu4IMnZnYNbgWXju9uew69Qu/GbjbxAaEoqUxBSn07OMrnUDeteu63XuCnNhcIfBeHHbi+jVuhfaRrTFmoI1+PzE57i5xc1Op2cZrzZ/PVr1QP5T+Si+VIy3v3wb07ZMQ96kvFqbAenWdqlFhRQD5BYQUgsCX1u+dzlGdxuNGFfMdTGpxYXUCmHx4sXiazrZzuXaMU/JTrluzKXWF/v27TP92ikp6sVX1ebBl6pq/+roV/jw2Id4etPTWHvfWnRr3q36v5HmrVS7UfuLmTNnKmNWtkgoKi7CjI0zsPkXm6/7P+O6MrqWJVKrKKu5PW4MiBmAl+9+GQDQr10/FJwtwNI9S2ttBKQcpTYPRtf5sWPHlDEr17i61i212pFyl9qZAPJ8lt5PVO2zSkpKxNerqa61S3lIa5FRayNpHTCaL97wxXUOyPPdqLWR1CJMer/3hZUPrMSUd6eg/SvtERIUgv7t+mNi74nYc3pP9X8jjbmUn7+2evFq8xcaElq9M7415lbsOrULS3YswbJxy3ySnL8rPF+ILUe24J0J7zidim10HvOq2huVNEKfln2w/4f9yPwqEy8Pftnp1Cyz5/QenC0/i/7L+lc/VumpxLbCbXh156u4/LvLCAkOcTBD67RztbvuU+1erXph/VfrHcrIHrrWDehbu87XOQB0bdEVeZPyUF5RjpLLJWjnaoeH334YXaK7OJ2aZXzS5LmK2+PG5crLvjykX8vMz0SbiDYY032M06k4Rrcxr8ntcaOissLpNCx1d+e7ceDpA7Uem5wzGT1b9cSzQ58N6DeEoR2H4tAPh2o99vUPXyMuKs6hjOyha92AvrXrfJ3XFBEagYjQCJy7eA6bDm/CH0b9wemULGN68zdnyxyM7jYasVGxKL1citUHViP3WC42PbbJl/n5LbfHjcz8TKQkpKBRsE/30H5L5zGvWfvBcwfx7pF3sePMDmSNMv/LHA2BK8yF3m1613osonEEWoa3vO7xQDPzZzMx5M0hePmTlzEhfgJ2ntyJ1794Ha+Pfd3p1Cyla92AvrXrfJ0DwKbDm+CBBz1a9sDhHw/jmc3PoGernpicONnp1CxjetdytvwsHt/wOE6XnUZUWBT6tu2LTY9twqiuo3yZn9/acmQLjhcfx5R+U5xOxTY6j3nN2l2NXegZ3RNZo7JwR8wdTqdGFhnYfiA2PLwBc7bOwe/zfo/O0Z2Rfm86kvsmO52apXStG9C7dp0VXy7GnK1zcKLkBFqEt8CDvR7E/Lvmo3FIY6dTs4zpzd/ypOW+zKPBuafrPfDM9Tidhq10HvOatUtfZtdB7qRcp1OwzdjuYzG2+1in07CdrnUDetdek07X+YT4CZgQP8HpNGxVp82fx/PTJqc+d01VcbvdytjVq1cNX1PlypUrylhpaakypqqh6vFrX9eb2s3+oPilS5fEuJlcjI7ly7orKyuN/yMTKirU36+T8gwOvnE7S7O1S/PLbO3StQAAFy5cUMbqO0ZWjLnEaD5LysrKlDEzedpd+8WLF5UxozGX1s7Ll9Xfs71RDXbXLeVntLZL58XMdWD32i6NmxGpduk6qs+Y13zM1+Nu9j0P8P81TrqWpf2Ir8+xEWnca/HUQVFRkQeAFv8UFRVpWbuudetcu65161y7rnXrXPu1detcuy51q8a9piCPx2h7+NP/yZw6dQoulytgf8XC4/GgtLQUMTExtT4pCvTada0b0Ld2XesG9K1d17oBfWtX1Q3oW3ug1w3I415TnTZ/RERERBQYfPLbvkRERETUMHDzR0RERKSROt3tq/Pfkwd67brWDehbu651A/rWrmvdgL618zt/+o05UPfv/PFuX4M7ZHSpXde6da5d17p1rl3XunWunXf76le3atxrqtMnfy6XCwBQVFSEyMjIujzFa717yz8pM3XqVFMxlZKSEnTs2LG61ipGtZ8/f155zDFj1L/5e/z4cWWsT58+BtmqTZs2rV75mK1bYvacGNW9dOnSeuVhxIoxf/TRR5Wx4uJiZWzhwoVirnfc4btfErFizIcOHWoql7Fj5Wa60vmMi4ur9+tZUbtZzz77rBjfvn27Mvbpp5/W67XM1r1//37lMYuKipQxqbaoqCgxV2n9Tk6u/y9t+NOYT5w4UYxLY7569Wpl7Ebrg6puwLvan3rqKWVMel+LjY0Vj+vL9d2KMf/kk0+UsaeffloZM3pfW7NmTb3yMCKNe0112vxVfTwaGRlp20UiflwJoEmTJsqYNzle+1GwUe1SQ8+QEPWPYUsfOTdqZP63gps2baqMSeelvnVLzJ6T0NBQ8bhWzT1fjrk0dlLtERERYo5W1O7LMZdqk4SFhYlxaQGz8zq3glHt0jk1m2N9627WrJnyWNJaI63fRnMlPDxcGWvoY964sfxzYdL7grRG1Gdtr/mYmdqldVpa/5xY33055tL5l+a70Zjb9b52Ld7wQURERKQRbv6IiIiINMLNHxEREZFGzH+5zAcSExOVscLCQvG5x44d820yJuXn5ytj+/btU8bmzp1r+jU7deqkjCUlJZk+bn2kp6crYzNnzjR1TOl8AfJ8SU1NNfWaZkhjnpeXZ+qYI0aMEON79+5VxqTz4ks5OTnKmNHYmX1ebm6uqZi/kNapJUuWmD6udNNR8+bNTR/3WitWrFDGpPyHDRumjEnrl9FrTpo0SXyuP5DWB+kaMjJv3jxlzNfXglRDVlaWqWMarY3S2A4fPtzUa9aXVPf48eNNHdNozKX3Lul91lv85I+IiIhII9z8EREREWmEmz8iIiIijXDzR0RERKQRbv6IiIiINMLNHxEREZFGLG/1It2+bbY9BGDcLsAu0q3hCQkJyph0235DILWakEjnxKhliXTO7Gz14gTpln+pNYYvSe07pN9rlca1IbRr8Ya0xs2YMUN8rjSuvmznIjHbRkiar0bXql21WSU7O1sZM/o9aqMWZ3aRrkvpWpeeJ50XQJ4X0vusL0k5SnsOKT+j3KU2NtJ7nrfXCT/5IyIiItIIN39EREREGuHmj4iIiEgj3PwRERERaYSbPyIiIiKNcPNHREREpBGftHqRbuvPyspSxubOnauMpaWlia85fvx4o7RsIbU8OXbsmDImtVCQngc07JYnRrf7m32udDu92XYVKtKt+ZmZmcrY5MmTlTGjFhDSdWRXqxeptYB0jqVrRFo7ALlVVENoCZKUlGT6ud5cK74irbPS2EmxvLw88TWla6gh6NevnzJmtLZL17l0LfiadM1K17rZGCCvY1I+dq0DZl/HqG7pPVtaA7ydD/zkj4iIiEgj3PwRERERaYSbPyIiIiKNcPNHREREpBFu/oiIiIg0ws0fERERkUZ80upFuuW4c+fOyti5c+dMv2Zubq6pfHxNuk27U6dOylh0dLQytnfvXvE1pdu/7Wr1IrUziIqKMnVM6XwB8i3z0nzwdasXiTT3vJmXQUFByphUu9SWxpek15HaNs2cOVM8rjTXpbr9hdSCKCUlRXyu1NLJLmbb+0gtS4zqtnP9lkjtRaS2JNK8zMnJEV8zISFBGfOX82IV6b1Lah3kD9eJVYxaA3mDn/wRERERaYSbPyIiIiKNcPNHREREpBFu/oiIiIg0ws0fERERkUa4+SMiIiLSCDd/RERERBrxSZ8/qRdUUlKSMtYQ+nQZkWo325dp8eLFpl/TLsOGDTP1PG960uXl5SljUh+oQCD1/5J6ydnV50/qtSXlIPXxA4AlS5YoY1Ldvu7tKM0vo16FKtLaCNjXs1Mi9bozGruGTprT0ryUxMXFiXF/eU+U+rhaNe5m+7j6ktm6pevEH96vb4Sf/BERERFphJs/IiIiIo1w80dERESkEW7+iIiIiDTCzR8RERGRRrj5IyIiItKIT1q9mNWpUycnX95yx44dU8bGjx+vjEm3jQNyiwu7SLevS609pPYV3swHX7f2kEjjYzZm1MpAeq4/zAcpv+LiYmXMqG1EVFSUMmbn+iHNW2nspLHJyckRX1NqLyNdY768FqTrXBpXqRVUVlaW+JorVqwwSssWUqsu6bxI+RcWFoqvKbWXsbOdldSGaMaMGcqYlL8UA+TzZte1LrXUkt7PpWvOKHdpjbByzPnJHxEREZFGTG/+thVuw7g14xDzpxgEpQUh+2C2D9PyX/Ny5yEoLajWPz1f7el0WrZ6bedr6JTeCU1eaoJB/28Qdp7c6XRKliu9XIrUjamIS49Du1fb4Z519+CLM184nZbldJ7vCz5ZgIFvDIRrgQtt/tgG49eOx6HvDzmdluUq3ZV4/h/Po/OSzgifH46u/90VL+a9CI/H43Rqlqs55nd9eBdm/u9MHCs95nRattFxba/y2s7XcPvbt6PHyh4Y//545H+X73RKljK9+SuvKEdC2wS8dv9rvsynQYhvHY/T/9/p6n+2T9nudEq2+WvBXzHro1mYO2wuvnjyCyS0TcC9q+7F2fKzTqdmqV/9/VfYfGQzVj6wEp8+9inuir0L4zeMx6myU06nZjld53teYR6mDZyGHb/cgc2/2Iwr7iu4Z9U9KK8odzo1Sy36dBEydmfg1dGv4qtpX2HRyEX4w2d/wJ93/tnp1CxXc8wzhmTgqucqnv78aVy8etHp1Cyn69oO/Lv2GQkz8N6499AruhdStqTg+4vfO52aZUxv/kZ3G42X7noJD/R6wJf5NAiNghvhpmY3Vf/Tqmkrp1OyzSs7XsET/Z/A5H6TcUvrW7B07FI0bdwUb+590+nULHPxykWs/3I9/jDyD7gz7k50ad4Fs382G12ad8Gb+wO37iq6zveNj23EpMRJiG8Tj4SbErAiaQWOFx/HntN7nE7NUp8VfYakHkkY030MOjXvhP+45T9wT9d7tPgUqOaY94jqgbR+aThz8Qy+PP+l06lZTse1vUpV7Q91ewjdmnfD/MHzER4Sjr8d/pvTqVmG3/kz4Zsfv0HMn2LQZUkXJL+TjOPFx51OyRYVlRXYc2oPRnYZWf1YcFAwRnYZic9PfO5gZta66r6KSk8lmjRqUuvxJiFNsOPUDoeyso+u8/1axZd/usGhRXgLhzOx1pCOQ7D16FZ8/cPXAIB9Z/Zh+/HtGH3zaIczs1/ZlTIAQFSo+sajQKDr2g6oax8aMxRffBe4X+1x9G7fhmhQ+0FYkbQCPVr1wOnS00jLS8MdmXeg4OkCuMJcTqdnqe8vfI9KTyXaRrSt9XjbiLY4+P1Bh7KynivMhcEdBuPFbS+iV+teCHOH4e2v38auM7vQJaqL0+lZSuf5XpPb40bqxlQM7TgUvdv0djodS82+fTZKLpeg56s9ERIcgkp3JebfNR/JfZOdTs1Wbo8b/1XwX0hskYibI292Oh1L6bq2A9fUXvnvx1s1aYV/Ff/LucQs5retXqRWAYDcIkK6Rd9bo7v9+/9++7bti6bnmuL+j+7Hf238LzwQV/uvwKV2LlKrBqPbu6U2A/7A7C37Ri1u5s6day4hH1j5wEpMeXcK2r/SHiFBIYhvEY9xnceh4IeCWnlLcy8vL08Zi4uLE19fOm9SGxJvXTvfB3UYhLj0OKz75zr8sv8v65SDUWsPSWZmpjJm53Uw7f1pKDhbcMPvOxq1q1ExGjepNYY0z7xtD7Hun+vw1oG3sPrB1YhvHY/8M/lI3ZSKGFcMUhJTqv+7vXv3Ko8hrW9GpBY4UgsSX3vj5Bs4fuk4tk/Zjg6RHWrFpNYe0rgavTctWbJEGZNaghi1ivIlqT7pWjBqQSRdz1a+p9dUc52N+iYKYefDqh+T1jFvWrd5M1+8wU/+vORq7EJss1gUlRc5nYrlWjVthZCgEHxb/m2tx78t/xY3NbvJoazs0bVFV+RNykN5RTn+efifaNO0DabnTUdss1inU7NV8ybN0b1ldxz+8bDTqdhm+gfT8d4372HbpG3XbQIC0TObn8HsobPxSO9HAAB92vZBYXEhFmxfUGvzF8h0G3Od13Zda+d3/rx04eoFnCg/gVZhgf8l+NCQUNwacyu2Htla/Zjb48bWI1sxuMNgBzOzT0RoBNo0bYPiy8XYdnIbRsaONH5SACmrKMO/fvwX2rnaOZ2K5TweD6Z/MB0bDm7APx7/BzpHd3Y6JVtcuHIBwUG13xpCgkLg9rgdysg+uo65zmu7rrWb/uSvrKKs1v/9Hz13FPln8tEivAViowL305DffvRbjOs+DnHN43Cq9BRm7ZyF4KBg3NfhPqdTs8Wsn81CSnYKBsQMwG3tb0P6jnSUXynH5MTJTqdmqU2HN8EDD3q07IHtp7Zjwe4F6BrVFQ/d/JDTqVnq2vk+N3cuQoJDMLH3RKdTs9y0D6Zh9YHVyHkkB64wF86UnQEARIVFIbxxuMPZWWdc93GY/8l8xEbFIr5NPPae3otXdryCKYlTnE7NcrqOOaDv2g7oWbvpzd/uU7sxImtE9Z9nfTQLAJCSkIIV41d4nZi/OlFyAhPXT8QPF39A66atER8Zj/+583/QIiyw7wCs8nDvh/Hdhe/wQu4LOFN2Bok3JWJj8ka0bdbW+MkNWPHlYszZOgcnSk4gKjQK98Xeh9/2/y0aBzd2OjVLXTvfb4+9HTt+uQOtI1o7nZrlMnZnAACGZw2v9XhmUiYmJU6yPR+7/Hn0n/H8x89j6gdTcbb8LGJcMXjy1ifxwrAXnE7NcrqOOaDv2g7oWbvpzd/wTsPhmRv4Hd+vtfY/1tb6sz/8rqrdpt82HdNvm+50GraaED8BE+InAJB/4zHQXDvfdaLj+gb8dHd7+n3pSL8v3elUbKfrmFfRcW2volvtddr8Vf2sT0lJiaXJ1HT16lUxfuXKFWXMTJ5Vz7n2J4yMai8rK1Me0+1Wf0emoqLCMBeV4GDffVXTbN11OeaNSD8RJZ0vALh8+bKp1zR6Tn1rLy0tVR7TaN6qGNUuHVeagzeqwYoxl+azNy5eVP+ygp1jbgVpPgPytVLfa8GKuqV5581PwV24cEEZawhjLh1Pet8yIq0B9Rnzmo+Zqf3SpUvKmJRjZWWlMmb03PJy9a/q2DXfpXkpMboW7Hpfu1FihoqKijwAtPinqKhIy9p1rVvn2nWtW+fada1b59qvrVvn2nWpWzXuNQV5PMb/i+Z2u3Hq1Cm4XC4EBQUZ/ecNksfjQWlpKWJiYmp9shbotetaN6Bv7brWDehbu651A/rWrqob0Lf2QK8bkMe9pjpt/oiIiIgoMLDPHxEREZFGuPkjIiIi0kid7vbV+e/JA712XesG9K1d17oBfWvXtW5A39r5nT/9xhyo+3f+eLevwR0yutSua906165r3TrXrmvdOtfOu331q1s17jXV6ZM/l8sFACgqKkJkZGRdnlIn58+fV8Zuv/128blRUVHK2Pvvv6+MNW/e/IaPl5SUoGPHjtW1VvGm9v379ytjjz76qDJWVFQkHrdjx47KWEFBgXFiNVhRt+Spp55SxqRxM4r37du33rmYrb2wsFB5TGlcjx8/royNGTNGzDU5OVkZu+OOO8TnXsts3dL1KuUv1b19+3Yx17i4ODFeX3bPd+mcGdW2evVqZcxovlzLirql60C6VhcsWCAeNzZW/fOg/rK2S5599lllbOnSpeJz33vvPWXMV9c54Mz6XlxcLD53zZo1PsvDijEfOnSoMia97xq9jnSd13fMAXnca6rT5q/q49HIyEifThSpsa1RI+OQkBBlTMrRKP9rPwr2pvZmzZopY940apaea3Z8fFm3JDQ0tM45XEs6n97kWN/apYtKmpdSfdJ5AYCIiAhlzK4xl65Xs3UbLVC+nHs12TXfjZp3S5o2baqM+cN1Lo1dkyZN6pzDtRrC2i4JCwsz/Vw7rvOaj9m5vjduLP8UphXXui/HXJqX9cnhWlaMeV1elzd8EBEREWmEmz8iIiIijXDzR0RERKQRbv6IiIiINFKnGz6cIN1JZhQ/duyYMpaYmGgyo/qbNGmSMqa6M80oBgD79u1TxqTaO3XqJB7XV9LT05WxrKwsZSwpKUk8rp1jJ5HOY1pamjIm3aGempoqvub48eOVsfz8fGXMl2OenZ2tjEnzTiLNlbrE/V1eXp7p52ZmZipjRteKHYYPH66MSfNOWhcBeZ5J82HevHnicetLulNbeq0lS5YoYwkJCeJr2rVGe0Nab6T1PSUlxYJs7CPNd2l9luYzAIwYMUIZ27t3rzLm7fshP/kjIiIi0gg3f0REREQa4eaPiIiISCPc/BERERFphJs/IiIiIo1w80dERESkEZ+0esnJyVHGpHYFubm5vnj56/hLSxCpPqmdi1HbD39o5yJZsWKFMia1O5Ge11CYbcFhNG7+0N5HavEgzVkpP6vWAH+xePFip1OwjDR23sw7aZ7ZSXofkVqNxcXFKWNSSxDAP9ZvI0atS1Qa+vputu2U2fMFyNcYW70QERERUZ1x80dERESkEW7+iIiIiDTCzR8RERGRRrj5IyIiItIIN39EREREGvFJqxepfYd0q3JxcbElr+kv5s2bp4xJ7QyMWh1I523SpEnKmF232kutPYYPH66MSe1vAp3ULgkAhg0bpoxJ59SXRowYoYxJ7S2kNjANZcylNg9SK4e8vDzTr2nXuJplVVuS8+fP2/qa58+fh9vtrlce0vvPkiVLlDGjVi/Sa5ptNeJr0nu6tA4EMmncpDZdgLy2G7V98wY/+SMiIiLSCDd/RERERBrh5o+IiIhII9z8EREREWmEmz8iIiIijXDzR0RERKQRn7R6kVoSSLdAS61Q0tLSxNeUnmsn6bZ36ZZ/byQlJSljVt4aXldSKxqpDYzRmAZCyxCVhIQEMe4P9UnzTmpPJLU7yczM9CYl2yQmJipj0honMWoDI72mXaQWREZtS6wQHR3t82M2b94ckZGR1z2elZWlfI5UuzfnxR+ucyPSGl5YWKiMGdUmtbKRWpj5A6k2o7Z0VrVMMsJP/oiIiIg0ws0fERERkUa4+SMiIiLSCDd/RERERBrh5o+IiIhII9z8EREREWmEmz8iIiIijfikz59ZUr8gI1JvQTtJeXz88cfKWHZ2tqkYIPdDcqpnUE1SX6N9+/aZigFy3Q25RxRg3BvMaE7YQer5lpKSooxJ88GJXnFmSNe5FJN6Uxr1+fOHa1nqPynNyaNHjypjK1asEF9T6pto1A/Tl6S+llJ90pw2WuP8oU+rEWleSn3+jPpWmq3d39d3o7qk9y4r8ZM/IiIiIo1w80dERESkEW7+iIiIiDTCzR8RERGRRrj5IyIiItIIN39EREREGnG01Ys3rQzy8/OVMaNbyu0i1Se1OzC6dd0fWkBIpFYHWVlZylhcXJx4XKmNwLx585QxVSuO0tJS8fVUpFYUUvsLqbWRUfsLfxjzc+fOKWPFxcXKmFWtXpo3b66M+UNrHECeKw2BNO+kmFS3dK0C8hrhD9cBYP68GJHmtL+QrlmpfZHReTE7Z+xq9SLtOaSYUSsXae2UnuttWyDTn/xtK9yGcWvGIeZPMQhKC0L2wWyvEmlIOqV3QlBa0HX/THt/mtOpWe5kyUk89s5jaPmHlgifH44+GX2w+9Rup9OyXMauDPTN6IvIBZGIzYjFPX+9B5uPbXY6Lcst+GQBBr4xEK4FLvym6Df477P/jdNXTjudli10XeN0Xt9qWrh9IYLSgpC6MdXpVGzBtT0SkQsiMXj5YHz4zYdOp2U505/8lVeUI6FtAqYkTsHP1/3clzn5vV1P7EKlp7L6zwVnCzBq5Sg8FP+Qg1lZ79zFcxj65lCM6DwCHyZ/iNZNW+ObH79BdJNop1OzXIfIDlg4ciG6teiG4pJirPlqDZL/noy8R/PQq2Uvp9OzTF5hHqYNnIaBMQOxPns91p9fjz99+yfMj5mPsOAwp9OzlK5rnK7rW027Tu7Csj3L0LdtX6dTsQXX9p/Wdg88yMrPQtLaJOx9ci/i28Q7nZ5lTG/+RncbjdHdRvsylwajdUTrWn9euH0hukZ3xbC4YQ5lZI9Fny5Cx6iOyEzKrH6sc3RnBzOyz7ge46r//XzIeTw/5Hm8uf9N7D69O6A3fxsf21j977tCd+GXLX+JGSdm4FjFMfRo0sPBzKyn6xqn6/pWpayiDMnvJOONcW/gpW0vOZ2OLbi2/9v8u+cjY3cGdpzYEdCbP97w4aWKygqs2r8KU/pNQVBQkNPpWOrdQ+9iQLsBeOhvD6HNH9ug37J+eGPPG06nZbtKdyXWH1qPC1cvYGC7gU6nY6uL7osAgIjgCIczITvotL5VmfbBNIzpNgYju4x0OhXbcG3/SaW7EmsL1qL8SjkGdxzsdDqWcvSGj0CQfTAb5y+dx6TESU6nYrkj544gY3cGZg2ehedufw67Tu3Cbzb+BqEhoUhJVP+2a6A48O0BDF4+GJeuXkJE4wisHLMSPVv2dDot27g9bqw5twbdwrqhQ2gHp9MhG+i0vgHA2oK1+OL0F9j1xC6nU7EV1/Z/r+3NQpthw8MbcEvrW5xOy1Lc/Hlp+d7lGN1tNGJcMU6nYjm3x40BMQPw8t0vAwD6teuHgrMFWLpnqRYLRI9WPZD/VD5OfHcCOYdzMHXzVLz34HvabABX/bgKJypO4LmbnnM6FbKJTutbUXERZmycgc2/2IwmjZo4nY6tuLb/tLYXXyrG21++jZTsFORNygvoDaCjmz/pFm2jVg3Sbc6q1h6Ab1sFFJ4vxJYjW/DOhHduGJdae0h5GLVCcEo7V7vrLoZerXph/Vfraz0m3Z4utTIwancikdr7qM51SUlJvV4jNCQUN7e4GY1KGmFG/AzsOrkL/73zv/Hy4Jer/xupBmk+GLUn8ubc+ML0D6bjEA5h6y+2Ii7q+pY8ZlvcSK0hjAwb5v/fQZPWKak9BADs27dPGbOj5YnR+iaR1naj1hxJSUn1fj1f2HN6D86Wn0X/Zf2rH6v0VGJb4Ta8uvNVXP7dZYQEhziSm9XqurYD8pyWrvXc3FwxB2lOe9MSqi6q1nYAuDXmVuw6tQtLdizBsnHLqv8baV8htWsxIs13K9vY8JM/L2TmZ6JNRBuM6T7G6VRsMbTjUBz64VCtx77+4esbbgZ04Pa4UVFZ4XQalvJ4PPi/H/5fbDi4Ae/+/F1tx1pHuq1vd3e+GweePlDrsck5k9GzVU88O/TZgN34AVzbr+X2uHG58rLTaVjK9OavrKIMh388XP3no+eOIv9MPlqEt0BsVKxPkvNnbo8bmfmZSElIQaNgPfbQM382E0PeHIKXP3kZE+InYOfJnXj9i9fx+tjXnU7NcnO2zMHobqMRGxWLg+cO4t0j72LHmR3IGqVuSBsIpn0wDasPrEbOIzlo1rgZvi3/FgAQGRaJ8EbhDmdnLZ3XOB3XN1eYC73b9K71WETjCLQMb3nd44GGa/tPa3vp5VKsPrAaucdysemxTU6nZinTV/XuU7sxImtE9Z9nfTQLAJCSkIIV41d4nZi/23JkC44XH8eUflOcTsU2A9sPxIaHN2DO1jn4fd7v0Tm6M9LvTUdy32SnU7Pc2fKzeHzD4zhddhquxi70jO6JrFFZuCPmDqdTs1TG7gwAwPCs4bUef23Ua3j0lkftT8hGOq9xOq5vOuPa/tPaHhUWhb5t+2LTY5swqusop1OzlOnN3/BOw+GZ6/FlLg3KPV3v0bL+sd3HYmz3sU6nYbvlScur/136XkugqTnHG/pPldWXzmucruvbtXIn5Tqdgm24tuuFff6IiIiINFKnT/48np/+D7C+d0caKS0tVcYqKyuVsZo51fe4qhqqHr/2uN7UXl5eroxJ9Rm9VnCw7/bsVtQtPefyZfWXaKUxNXLlypV652O2dml+Xb16VRlzu93KmJS/lAtQ//lgtm4pByl/o2vZLOlc23mdS8rKypQxo/Ny4cIFZay+edpdtzQfpDXAilz8qXajMfdlLqq6az7m69qlsTWqXTpvFy9eVMZuVIMVY+7N+5PEzHsXoF73pXGvxVMHRUVFHgBa/FNUVKRl7brWrXPtutatc+261q1z7dfWrXPtutStGveagjwe4+2s2+3GqVOn4HK5AvYnfjweD0pLSxETE1NrRx3otetaN6Bv7brWDehbu651A/rWrqob0Lf2QK8bkMe9pjpt/oiIiIgoMPCGDyIiIiKN1OmGD50/Kg302nWtG9C3dl3rBvStXde6AX1r51/76jfmQN3/2pc3fBh8SVKX2nWtW+fada1b59p1rVvn2nnDh351q8a9pjp98udyuQAARUVFiIyMrMtT6kRqGvvoo/KvB9xxh/qXFZ5++mllrHnz5jd8vKSkBB07dqyutYpR7Z988ompPIqKipQxI0OHDlXGVq9erYzdqHazdUueffZZZWz79u3KmNGPYy9atEgZGzOm/r8/akXtkokTJypjH3zwgfhcaVzrW7sVde/fv18Zmz17tjL26aefiseVztnSpUuNE7tGQxpz6bzNmTOnXnmYrVtaoxcsWKCMSWNjdH6l+dwQxly6Foze16T1UfXepaKqGzCuvbCwUHnc22+/XXxNs3r3Vv+EnrT+xcXF3TAPX4+5dC306dNHGYuNlX8K0mgNrC9p3Guq0+av6uPRyMhIn14kUt+zRo3k1MLCwpQxKUej/K/9KNio9oiICOWxfNmPrybp3Jitvb51S6SxCQlR/zi60flq2rSpMubNvPRl7ZLGjRubfq4Vtfuy7mbNmiljRteyJDQ0VBkL9DE3u8ZJ6lu3tEZL+dUnh2s19DGXrgWjNc6b9y6VG51vo9qljYNVf10qvTdI+dj1viZdC9I5keqqysUKRuPEGz6IiIiINMLNHxEREZFGuPkjIiIi0gg3f0REREQaMf9NbB/Iz89XxvLy8sTnSvHU1FSTGdVfp06dTMWkHNPT08XXlGrPzs5WxiZNmiQetz5yc3OVsSVLlihjKSkpypg0HwBg/PjxypinAfxQTX3v1vM3x44dU8aksZGug2HDhpl+TX+xYsUKZSwnJ0cZS0hIEI8rnVO7SOuJdJ3PnTtXGTO6DmbOnKmMSetmYmKieFy7SOusdC34E2mMzF7r0nUCAPv27TP13Hnz5onHtYPUqUKqC5DXiKSkJNM5GeEnf0REREQa4eaPiIiISCPc/BERERFphJs/IiIiIo1w80dERESkEW7+iIiIiDRieasX6ceQvWnJIt0CbWdLDenWdqkdinR7t/Sj2oDcLsWX7Vwkw4cPV8akFhZS6whvxk2aZ3bOB2nMs7KybMvDClLLAmk+SG0ajOarNK7+wmw7GqNWLv7QukQaH+lalsbcaH2T1nZ/aZUiteOSrhPpnAHyXLJzPkhrplHLFpW0tDQxHhUVpYzZ2b5NxWzdRqxs5yLhJ39EREREGuHmj4iIiEgj3PwRERERaYSbPyIiIiKNcPNHREREpBFu/oiIiIg04pNWL1I7BqlVgHRLvDev2RBIt7Ub8YcWEJL8/HxTMalNCgDMnDlTGbOzRYLUokNq4eONuLg4S45bH1JLAikmXatGYy6da2nM7WwJYtS+Q8WutkzekMZOOv9SO5fMzEzxNf3lvEhr1bx585Qxb1p39OvXTxk7evSoMuYvLXC8IbVzsbNdl4rZVi9S6zMn8ZM/IiIiIo1w80dERESkEW7+iIiIiDTCzR8RERGRRrj5IyIiItIIN39EREREGrG81YsUmzt3rjKWlpYmvmYg3Npulj/c9m6W1HbFm/Y9dra/mTx5sqk8pFYBUmsMwP/HXGp9YXQtS5YsWaKMSfPFbFsGM6SWJxKjVlf+sMalp6crY2br9vdWVVWka7K4uNjUMY3a3Eiktkj+0h5HYtSuSrpmpfXFl6T57k1rOn/ET/6IiIiINMLNHxEREZFGuPkjIiIi0gg3f0REREQa4eaPiIiISCPc/BERERFphJs/IiIiIo34pM+f1I9K6k0kkfrtGL1mQyD1uoqKihKfm52drYw1hH5PKt70/8rPz7fkuDeSlJRkKmZn7zm7mb0eExISxLg0n1NTU029phlSTzuzPd/Gjx8vxqXrXJpnvtSvXz9lTOo9KdVm1LNNqttO0jmW+vVJ13leXp74mtL10FD6I6oY5Z+Tk6OMST09fdkDVVpvpL2MlLu/4id/RERERBrh5o+IiIhII9z8EREREWmEmz8iIiIijXDzR0RERKQRbv6IiIiINOKTVi9mSbdOG7VPGD58uG+TMUm6BV1qV+NN6whf3tpullS31PYjKytLGdu7d6/pfPzhnBiRWh0UFhbal4gFpBYJkydPVsbS0tLE49rV0sSINL9SUlKUMWm+G5kxY4YyZtd5kV5Hqlua6zNnzhRf0862TWZJ811qc2PUEkk6rp21S+9P0nuvdJ3s27fPknx8eV6k/KX3c6nVizd1W8n0J3/bCrdh3JpxiPlTDILSgpB9MNuHafmvjF0Z6JvRF5ELIhG5IBL3/PUebD622em0bFN6uRSpG1PR580+aPdqO9yz7h58ceYLp9OynK7zvVN6JwSlBV33z7T3pzmdmi1OlpzEY+88hi7LuqDdq+0wZNUQ7P3W/P+kNASV7ko8/4/n0XlJZ4TPD0fX/+6KF/NehMfjcTo1Wy3cvhBBaUFI3ZjqdCqWu/Z97ecf/By5J3KdTss2Oq7vpj/5K68oR0LbBExJnIKfr/u5L3Pyax0iO2DhyIXo1qIbPPBg2f8uQ/Lfk5H3aB56tezldHqW+9Xff4WCswVYeu9StItoh3UH12H8hvHY8YsdiGkW43R6ltF1vu96YhcqPZXVfy44W4BRK0fhofiHHMzKHucunsPQN4diROcR+FvS39AqvBX+df5faB7W3OnULLXo00XI2J2BrPFZiG8Tj92ndmNyzmRENYnCbwb9xun0bLHr5C4s27MMfdv2dToVW1z7vrYkbwl+/fGv8d7Y99A9urvT6VlOx/Xd9OZvdLfRGN1ttC9zaRDG9RhX68/PD3keb+5/E7tP7w74zd/FKxex/sv1yHkkB0PbDAUAzP7ZbGw8uhFv7n8TvxvyO4cztI6u8711ROtaf164fSG6RnfFsLhhDmVkn0WfLkLHqI7ITMqs/ppDXFScs0nZ4LOiz5DUIwljuo8BAHRq3glrCtZg58mdDmdmj7KKMiS/k4w3xr2Bl7a95HQ6trj2fe2Z/s/grUNvYe/3e7XY/Om4vvOGDy9Uuiux/tB6XLh6AQPbDXQ6HctddV9FpacSTRo1qfV4k5Am2HFqh0NZkV0qKiuwav8qTOk3BUFBQU6nY7l3D72LAe0G4KG/PYRur3fDnavvRFaB+e/wNRRDOg7B1qNb8fUPXwMA9p3Zh+3Ht2P0zXq8OU77YBrGdBuDkV1GOp2KIyrdlfj70b/j4tWL6N+6v9PpkEUcveGjoTrw7QEMXj4Yl65eQkTjCKwcsxI9W/Z0Oi3LucJcGNxhMF7c9iIyRmagTdM2ePvrt7HrzC50ieridHpkseyD2Th/6TwmJU5yOhVbHDl3BBm7MzBr8Cz834T/iy++/QKzc2cjNDgUE2+Z6HR6lpl9+2yUXC5Bz1d7IiQ4BJXuSsy/az6S+yY7nZrl1hasxRenv8CuJ3Y5nYrtar6vNW3UFEtHLEW35t2cTossws2fCT1a9UD+U/kovlSMVXtXYermqXjvwfe02ACufGAlprw7BbcsvwUhQSFIaJOAB7s/iH1n/fOOJvKd5XuXY3S30YhxBe53O2tye9wYEDMAL9/9Ms6fP4++bfriqx++QuaBzIDe/K375zq8deAtrH5wNeJbxyP/TD5SN6UixhWDlET1Hb4NXVFxEWZsnIHNv9h83d9u6KDm+9ryz5fjt9t/i7X3reUGMEA5uvmTbqtOSEiwL5F6Cg0Jxc0tbgYAnNh1Av8I+QfmfjgXUztOrfXfGbWxUImKihLj0i3nVuvaoivyJuWhvKIcJZdL0M7VDg+//TBubnVz9XjOmzdP+XypPYRRixup9YVRCwV/ILUkkFoFAMCKFSuUMel8+0rh+UJsObIF70x454ZxKX/pWvaXVi430s7VDre0vgXAv9eqxPaJeO/Ie7XWLmlspBYVeXl54utL7ZSs9MzmZzB76Gw80vsRAECftn1QWFyIBdsX1Nr8SS0/pHYuc+fOFV/fqXYue07vwdnys+i/7N9/1VnpqcS2wm14deeruPy7ywgJDjE8jjRuRmuck2q+r7W8tSX2/7AfmV9l4uXBL9f676T6pJZVcXHy92WXLFmijPlDix9pvyLVZtTGy6nWRvzkzwc88OCK+4rTadgqIjQCEaEROHfxHDYd3oQ/jPqD0ymRhTLzM9Emok31TQA6GNpxKA79cKjWY1//8HXA3/Rx4coFBAfV/jp4SFAI3B63QxnZ4+7Od+PA0wdqPTY5ZzJ6tuqJZ4c+W6eNXyBxe9yoqKxwOg2yiOnNX1lFGQ7/eLj6z0fPHUX+mXy0CG+B2KhYnyTnj+ZsmYPR3UYjNioWpZdLsfLUShSUFWBuV/n/ZgPFpsOb4IEHPVr2wOEfD+OZzc+gZ6uemJyobuQbCHSd78BPbwKZ+ZlISUhBo2B9/n9x5s9mYsibQ/DyJy9jQvwE7Dy5E69/8TpeH/u606lZalz3cZj/yXzERsUivk089p7ei1d2vIIpiVOcTs1SrjAXerfpXeuxiMYRaBne8rrHA82172sZezKw48wOZI0K/BucAD3Xd9Mr+e5TuzEia0T1n2d9NAsAkJKQghXjV3idmL86W34Wj294HKfLTiMqLArtgtthbte5SHQlOp2aLYovF2PO1jk4UXICLcJb4MFeD2L+XfPROKSx06lZStf5DgBbjmzB8eLjmNIvsN/8rzWw/UBseHgD5mydg9/n/R6dozsj/d70gL/x4c+j/4znP34eUz+YirPlZxHjisGTtz6JF4a94HRqZJFr39e6R3VH1qgs3BFzh9Op2ULH9d305m94p+HwzNWr4zsALE9aXuvPRt/VCjQT4idgQvwEp9Owna7zHQDu6XqPtrWP7T4WY7uPdToNW7nCXEi/Lx3p96U7nYrjciflOp2CLa59X5O+qxqIdFzf2eePiIiISCN1+uSv6jcdS0pKfPriZWVlylhlZaUyBgDl5eXKmJk8q55z7e9XGtV+4cKFer+WEaPf0JTqCw6u337ebN2SS5cuKWPe/D7o5cuXlTE7x9wsKX9vnlvfPK2oW7oOpGvZ1+fYiN1jfvXqVdPPla4VfxjzK1fM3eRmdB34egzsHvPS0lLTz5XWTl+Nec3HVMeUajC7hrvd8g1D0hriD/Ndeo5RbRJpH+TL97XreOqgqKjIA0CLf4qKirSsXde6da5d17p1rl3XunWu/dq6da5dl7pV415TkMdjvI13u904deoUXC5XwP6sk8fjQWlpKWJiYmp9ehbotetaN6Bv7brWDehbu651A/rWrqob0Lf2QK8bkMe9pjpt/oiIiIgoMPCGDyIiIiKNcPNHREREpBFu/oiIiIg0ws0fERERkUa4+SMiIiLSCDd/RERERBrh5o+IiIhII/8/5xjfkLVlY+gAAAAASUVORK5CYII=",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
"fig, axes = plt.subplots(10, 10, figsize=(8, 8),\n",
" subplot_kw={'xticks':[], 'yticks':[]},\n",
" gridspec_kw=dict(hspace=0.1, wspace=0.1))\n",
"\n",
"for i, ax in enumerate(axes.flat):\n",
" ax.imshow(digits.images[i], cmap='binary', interpolation='nearest')\n",
" ax.text(0.05, 0.05, str(digits.target[i]),\n",
" transform=ax.transAxes, color='green')"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "awvR-BwuhBiU"
},
"source": [
"In order to work with this data within Scikit-Learn, we need a two-dimensional, `[n_samples, n_features]` representation.\n",
"We can accomplish this by treating each pixel in the image as a feature: that is, by flattening out the pixel arrays so that we have a length-64 array of pixel values representing each digit.\n",
"Additionally, we need the target array, which gives the previously determined label for each digit.\n",
"These two quantities are built into the digits dataset under the `data` and `target` attributes, respectively:"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"deletable": true,
"editable": true,
"id": "z1uEi5uuhBiU",
"jupyter": {
"outputs_hidden": false
},
"outputId": "2b27d627-5bfa-447c-9c7f-f023e58defe8"
},
"outputs": [
{
"data": {
"text/plain": [
"(1797, 64)"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X = digits.data\n",
"X.shape"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"deletable": true,
"editable": true,
"id": "VoxIakeGhBiU",
"jupyter": {
"outputs_hidden": false
},
"outputId": "29a582c6-228d-4a83-84dd-ff7dc4d2d1bb"
},
"outputs": [
{
"data": {
"text/plain": [
"(1797,)"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"y = digits.target\n",
"y.shape"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "Xu9n-N-3hBiV"
},
"source": [
"We see here that there are 1,797 samples and 64 features."
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "TaqdiYgShBiV"
},
"source": [
"### Unsupervised Learning Example: Dimensionality Reduction\n",
"\n",
"We'd like to visualize our points within the 64-dimensional parameter space, but it's difficult to effectively visualize points in such a high-dimensional space.\n",
"Instead, we'll reduce the number of dimensions, using an unsupervised method.\n",
"Here, we'll make use of a manifold learning algorithm called Isomap and transform the data to two dimensions:"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"deletable": true,
"editable": true,
"id": "ozy2SgS0hBiV",
"jupyter": {
"outputs_hidden": false
},
"outputId": "67dce8d6-9afc-4743-c9bb-db06bafc314a"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(1797, 2)\n"
]
}
],
"source": [
"from sklearn.manifold import Isomap\n",
"iso = Isomap(n_components=2)\n",
"iso.fit(digits.data)\n",
"data_projected = iso.transform(digits.data)\n",
"print(data_projected.shape)"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "sZMmGRyJhBiV"
},
"source": [
"We see that the projected data is now two-dimensional.\n",
"Let's plot this data to see if we can learn anything from its structure (see the following figure):"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {
"deletable": true,
"editable": true,
"id": "28JdsQMWhBiV",
"jupyter": {
"outputs_hidden": false
},
"outputId": "b16c1ba1-7ddc-482b-b72d-ffe5debffa42"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(data_projected[:, 0], data_projected[:, 1], c=digits.target,\n",
" edgecolor='none', alpha=0.9,\n",
" cmap=plt.cm.get_cmap('tab20', 10))\n",
"plt.colorbar(label='digit label', ticks=range(10))\n",
"plt.clim(-0.5, 9.5);"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "mPPDCEGwhBiV"
},
"source": [
"This plot gives us some good intuition into how well various numbers are separated in the larger 64-dimensional space. For example, zeros and ones have very little overlap in the parameter space.\n",
"Intuitively, this makes sense: a zero is empty in the middle of the image, while a one will generally have ink in the middle.\n",
"On the other hand, there seems to be a more or less continuous spectrum between ones and fours: we can understand this by realizing that some people draw ones with \"hats\" on them, which causes them to look similar to fours.\n",
"\n",
"Overall, however, despite some mixing at the edges, the different groups appear to be fairly well localized in the parameter space: this suggests that even a very straightforward supervised classification algorithm should perform suitably on the full high-dimensional dataset.\n",
"Let's give it a try."
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "awLeIEdYhBiW"
},
"source": [
"### Classification on Digits\n",
"\n",
"Let's apply a classification algorithm to the digits data.\n",
"As we did with the Iris data previously, we will split the data into training and testing sets and fit a Gaussian naive Bayes model:"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {
"deletable": true,
"editable": true,
"id": "p0747EGahBiW",
"tags": []
},
"outputs": [],
"source": [
"Xtrain, Xtest, ytrain, ytest = train_test_split(X, y, random_state=0)"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {
"deletable": true,
"editable": true,
"id": "c3DHvo1hhBiW",
"tags": []
},
"outputs": [],
"source": [
"from sklearn.naive_bayes import GaussianNB\n",
"model = GaussianNB()\n",
"model.fit(Xtrain, ytrain)\n",
"y_model = model.predict(Xtest)"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "LPdrxdIOhBiW"
},
"source": [
"Now that we have the model's predictions, we can gauge its accuracy by comparing the true values of the test set to the predictions:"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {
"deletable": true,
"editable": true,
"id": "aPYXJTl_hBiW",
"jupyter": {
"outputs_hidden": false
},
"outputId": "275e7b92-99bf-4148-e92a-bc31facbde5d"
},
"outputs": [
{
"data": {
"text/plain": [
"0.8333333333333334"
]
},
"execution_count": 51,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from sklearn.metrics import accuracy_score\n",
"accuracy_score(ytest, y_model)"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "2q8yXy2chBiW"
},
"source": [
"With even this very simple model, we find about 83% accuracy for classification of the digits!\n",
"However, this single number doesn't tell us where we've gone wrong. One nice way to do this is to use the *confusion matrix*, which we can compute with Scikit-Learn and plot with Seaborn (see the following figure):"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {
"deletable": true,
"editable": true,
"id": "_SbknytVhBiW",
"jupyter": {
"outputs_hidden": false
},
"outputId": "383984d2-1b9f-49bc-f528-3e2c6ac08507"
},
"outputs": [
{
"data": {
"text/plain": [
"Text(113.9222222222222, 0.5, 'true value')"
]
},
"execution_count": 54,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from sklearn.metrics import confusion_matrix\n",
"\n",
"mat = confusion_matrix(ytest, y_model)\n",
"\n",
"sns.heatmap(mat, square=True, annot=True, cbar=False, cmap='Blues')\n",
"plt.xlabel('predicted value')\n",
"plt.ylabel('true value')"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "P6B1k8ukhBiW"
},
"source": [
"This shows us where the mislabeled points tend to be: for example, many of the twos here are misclassified as either ones or eights.\n",
"\n",
"Another way to gain intuition into the characteristics of the model is to plot the inputs again, with their predicted labels.\n",
"We'll use blue for correct labels and red for incorrect labels; see the following figure:"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {
"deletable": true,
"editable": true,
"id": "pqv1uju0hBiW",
"jupyter": {
"outputs_hidden": false
},
"outputId": "7d28e203-6d39-4c72-fd52-d7760326e9df"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, axes = plt.subplots(10, 10, figsize=(8, 8),\n",
" subplot_kw={'xticks':[], 'yticks':[]},\n",
" gridspec_kw=dict(hspace=0.1, wspace=0.1))\n",
"\n",
"test_images = Xtest.reshape(-1, 8, 8)\n",
"\n",
"for i, ax in enumerate(axes.flat):\n",
" ax.imshow(test_images[i], cmap='binary', interpolation='nearest')\n",
" ax.text(0.05, 0.05, str(y_model[i]),\n",
" transform=ax.transAxes,\n",
" color='blue' if (ytest[i] == y_model[i]) else 'red')"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true,
"id": "2p8PWjP7hBiW"
},
"source": [
"Examining this subset of the data can give us some insight into where the algorithm might be not performing optimally.\n",
"To go beyond our 83% classification success rate, we might switch to a more sophisticated algorithm such as support vector machines, random forests, or another classification approach."
]
}
],
"metadata": {
"anaconda-cloud": {},
"colab": {
"provenance": []
},
"jupytext": {
"formats": "ipynb,md"
},
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.3"
}
},
"nbformat": 4,
"nbformat_minor": 0
}