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ashishsahu1/heart_sentiment.ipynb

Created August 12, 2023 11:40
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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [],
"authorship_tag": "ABX9TyO5yjRZoxIFbbLMPC8hN66a",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/ashishsahu1/5c2ce0658c690d6ccac385bdc068956e/heart_sentiment.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"source": [
"# SENTIMENT ANALYSIS USING NLP\n",
"\n",
"\n"
],
"metadata": {
"id": "tXre6NXD96Ic"
}
},
{
"cell_type": "code",
"source": [
"import pandas as pd\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer\n",
"from sklearn.naive_bayes import MultinomialNB\n",
"from sklearn.svm import SVC\n",
"from sklearn.metrics import accuracy_score\n",
"\n",
"# Load and preprocess data\n",
"data = pd.read_csv('dataset.csv')\n",
"data['sentiment'] = data['sentiment'].apply(lambda x: 1 if x == 'positive' else 0)\n",
"\n",
"# Split data\n",
"train_data, test_data = train_test_split(data, test_size=0.2, random_state=42)\n",
"\n",
"# Train Naive Bayes model using CountVectorizer\n",
"count_vectorizer = CountVectorizer()\n",
"X_train_count = count_vectorizer.fit_transform(train_data['statement'])\n",
"y_train = train_data['sentiment']\n",
"naive_bayes_count_model = MultinomialNB()\n",
"naive_bayes_count_model.fit(X_train_count, y_train)\n",
"\n",
"# Train Naive Bayes model using TF-IDF\n",
"tfidf_vectorizer = TfidfVectorizer()\n",
"X_train_tfidf = tfidf_vectorizer.fit_transform(train_data['statement'])\n",
"naive_bayes_tfidf_model = MultinomialNB()\n",
"naive_bayes_tfidf_model.fit(X_train_tfidf, y_train)\n",
"\n",
"# Train SVM model using CountVectorizer\n",
"svm_count_model = SVC()\n",
"svm_count_model.fit(X_train_count, y_train)\n",
"\n",
"# Train SVM model using TF-IDF\n",
"svm_tfidf_model = SVC()\n",
"svm_tfidf_model.fit(X_train_tfidf, y_train)\n",
"\n",
"# Evaluate models\n",
"X_test_count = count_vectorizer.transform(test_data['statement'])\n",
"naive_bayes_count_predictions = naive_bayes_count_model.predict(X_test_count)\n",
"svm_count_predictions = svm_count_model.predict(X_test_count)\n",
"\n",
"X_test_tfidf = tfidf_vectorizer.transform(test_data['statement'])\n",
"naive_bayes_tfidf_predictions = naive_bayes_tfidf_model.predict(X_test_tfidf)\n",
"svm_tfidf_predictions = svm_tfidf_model.predict(X_test_tfidf)\n",
"\n",
"# Calculate and print accuracies\n",
"naive_bayes_count_accuracy = accuracy_score(test_data['sentiment'], naive_bayes_count_predictions)\n",
"svm_count_accuracy = accuracy_score(test_data['sentiment'], svm_count_predictions)\n",
"naive_bayes_tfidf_accuracy = accuracy_score(test_data['sentiment'], naive_bayes_tfidf_predictions)\n",
"svm_tfidf_accuracy = accuracy_score(test_data['sentiment'], svm_tfidf_predictions)\n",
"\n",
"print(\"Naive Bayes Model Accuracy (CountVectorizer):\", naive_bayes_count_accuracy)\n",
"print(\"SVM Model Accuracy (CountVectorizer):\", svm_count_accuracy)\n",
"print(\"Naive Bayes Model Accuracy (TF-IDF):\", naive_bayes_tfidf_accuracy)\n",
"print(\"SVM Model Accuracy (TF-IDF):\", svm_tfidf_accuracy)\n",
"\n",
"# Test custom input\n",
"custom_input = \"The patient's blood pressure is seems normal\"\n",
"\n",
"custom_input_count = count_vectorizer.transform([custom_input])\n",
"custom_sentiment_naive_bayes_count = \"positive\" if naive_bayes_count_model.predict(custom_input_count)[0] == 1 else \"negative\"\n",
"custom_sentiment_svm_count = \"positive\" if svm_count_model.predict(custom_input_count)[0] == 1 else \"negative\"\n",
"custom_sentiment_naive_bayes_tfidf = \"positive\" if naive_bayes_tfidf_model.predict(tfidf_vectorizer.transform([custom_input]))[0] == 1 else \"negative\"\n",
"custom_sentiment_svm_tfidf = \"positive\" if svm_tfidf_model.predict(tfidf_vectorizer.transform([custom_input]))[0] == 1 else \"negative\"\n",
"\n",
"print(\"Custom Input Sentiment (Naive Bayes - CountVectorizer):\", custom_sentiment_naive_bayes_count)\n",
"print(\"Custom Input Sentiment (SVM - CountVectorizer):\", custom_sentiment_svm_count)\n",
"print(\"Custom Input Sentiment (Naive Bayes - TF-IDF):\", custom_sentiment_naive_bayes_tfidf)\n",
"print(\"Custom Input Sentiment (SVM - TF-IDF):\", custom_sentiment_svm_tfidf)\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "73pOSO4j9_jW",
"outputId": "ad8dcd9c-f389-45c1-8655-c0170625aa71"
},
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Naive Bayes Model Accuracy (CountVectorizer): 0.974169741697417\n",
"SVM Model Accuracy (CountVectorizer): 0.9704797047970479\n",
"Naive Bayes Model Accuracy (TF-IDF): 0.9704797047970479\n",
"SVM Model Accuracy (TF-IDF): 0.985239852398524\n",
"Custom Input Sentiment (Naive Bayes - CountVectorizer): positive\n",
"Custom Input Sentiment (SVM - CountVectorizer): positive\n",
"Custom Input Sentiment (Naive Bayes - TF-IDF): positive\n",
"Custom Input Sentiment (SVM - TF-IDF): positive\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"from sklearn.model_selection import train_test_split\n",
"from tensorflow.keras.models import Sequential\n",
"from tensorflow.keras.layers import Dense, Embedding, LSTM\n",
"from tensorflow.keras.preprocessing.text import Tokenizer\n",
"from tensorflow.keras.preprocessing.sequence import pad_sequences\n",
"\n",
"# Load and preprocess data\n",
"data = pd.read_csv('dataset.csv')\n",
"data['sentiment'] = data['sentiment'].apply(lambda x: 1 if x == 'positive' else 0)\n",
"\n",
"# Split data\n",
"train_data, test_data = train_test_split(data, test_size=0.2, random_state=42)\n",
"\n",
"# Tokenize and pad sequences\n",
"tokenizer = Tokenizer()\n",
"tokenizer.fit_on_texts(train_data['statement'])\n",
"train_sequences = tokenizer.texts_to_sequences(train_data['statement'])\n",
"test_sequences = tokenizer.texts_to_sequences(test_data['statement'])\n",
"train_padded = pad_sequences(train_sequences, padding='post')\n",
"test_padded = pad_sequences(test_sequences, padding='post')\n",
"\n",
"# Build and train custom model\n",
"model = Sequential()\n",
"model.add(Embedding(input_dim=len(tokenizer.word_index) + 1, output_dim=128, input_length=train_padded.shape[1]))\n",
"model.add(LSTM(64))\n",
"model.add(Dense(1, activation='sigmoid'))\n",
"model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])\n",
"model.fit(train_padded, train_data['sentiment'], epochs=10, validation_data=(test_padded, test_data['sentiment']))\n",
"\n",
"# Evaluate custom model\n",
"custom_predictions = model.predict(test_padded)\n",
"custom_accuracy = accuracy_score(test_data['sentiment'], (custom_predictions >= 0.5).astype(int))\n",
"print(\"Custom Model Accuracy:\", custom_accuracy)\n",
"\n",
"# Take custom input and provide sentiments using the custom model\n",
"while True:\n",
" custom_input = input(\"Enter a statement (or type 'exit' to quit): \")\n",
" if custom_input.lower() == 'exit':\n",
" break\n",
"\n",
" custom_sequences = tokenizer.texts_to_sequences([custom_input])\n",
" custom_padded = pad_sequences(custom_sequences, padding='post', maxlen=train_padded.shape[1])\n",
"\n",
" custom_pred_custom = model.predict(custom_padded)\n",
" custom_sentiment_custom = \"positive\" if custom_pred_custom >= 0.5 else \"negative\"\n",
"\n",
" print(\"Custom Model Sentiment:\", custom_sentiment_custom)\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "4q0hZelT-dYv",
"outputId": "055dd713-a445-43e0-d8d1-b8a85c45ba27"
},
"execution_count": 2,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/10\n",
"34/34 [==============================] - 10s 77ms/step - loss: 0.5645 - accuracy: 0.6691 - val_loss: 0.2191 - val_accuracy: 0.9373\n",
"Epoch 2/10\n",
"34/34 [==============================] - 1s 39ms/step - loss: 0.1630 - accuracy: 0.9464 - val_loss: 0.1081 - val_accuracy: 0.9742\n",
"Epoch 3/10\n",
"34/34 [==============================] - 2s 54ms/step - loss: 0.0488 - accuracy: 0.9880 - val_loss: 0.1207 - val_accuracy: 0.9705\n",
"Epoch 4/10\n",
"34/34 [==============================] - 2s 53ms/step - loss: 0.0084 - accuracy: 0.9991 - val_loss: 0.1455 - val_accuracy: 0.9705\n",
"Epoch 5/10\n",
"34/34 [==============================] - 1s 37ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.1632 - val_accuracy: 0.9668\n",
"Epoch 6/10\n",
"34/34 [==============================] - 1s 27ms/step - loss: 0.0014 - accuracy: 1.0000 - val_loss: 0.1743 - val_accuracy: 0.9705\n",
"Epoch 7/10\n",
"34/34 [==============================] - 1s 20ms/step - loss: 9.9792e-04 - accuracy: 1.0000 - val_loss: 0.1832 - val_accuracy: 0.9705\n",
"Epoch 8/10\n",
"34/34 [==============================] - 1s 22ms/step - loss: 7.5056e-04 - accuracy: 1.0000 - val_loss: 0.1916 - val_accuracy: 0.9705\n",
"Epoch 9/10\n",
"34/34 [==============================] - 1s 22ms/step - loss: 5.9071e-04 - accuracy: 1.0000 - val_loss: 0.1988 - val_accuracy: 0.9705\n",
"Epoch 10/10\n",
"34/34 [==============================] - 1s 22ms/step - loss: 4.8041e-04 - accuracy: 1.0000 - val_loss: 0.2050 - val_accuracy: 0.9705\n",
"9/9 [==============================] - 1s 5ms/step\n",
"Custom Model Accuracy: 0.9704797047970479\n",
"Enter a statement (or type 'exit' to quit): The patient's blood pressure is seems normal\n",
"1/1 [==============================] - 0s 26ms/step\n",
"Custom Model Sentiment: positive\n",
"Enter a statement (or type 'exit' to quit): exit\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
"models = ['Naive Bayes (Count)', 'Naive Bayes (TF-IDF)', 'SVM (Count)', 'SVM (TF-IDF)', 'Custom Neural Network']\n",
"accuracies = [naive_bayes_count_accuracy, naive_bayes_tfidf_accuracy, svm_count_accuracy, svm_tfidf_accuracy, custom_accuracy]\n",
"\n",
"plt.bar(models, accuracies, color=['blue', 'orange', 'green', 'red', 'purple'])\n",
"plt.xlabel('Models')\n",
"plt.ylabel('Accuracy')\n",
"plt.title('Model Accuracies')\n",
"plt.ylim(0, 1.1)\n",
"\n",
"# Print accuracies on the bars\n",
"for i, v in enumerate(accuracies):\n",
" plt.text(i, v + 0.01, f'{v:.3f}', ha='center', va='bottom')\n",
"\n",
"plt.xticks(rotation=45)\n",
"plt.tight_layout()\n",
"plt.show()\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 487
},
"id": "zzAFFXCEBE76",
"outputId": "a4457909-d7b7-40e4-c365-910a90c30174"
},
"execution_count": 3,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"import pandas as pd\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer\n",
"from sklearn.naive_bayes import MultinomialNB\n",
"from sklearn.svm import SVC\n",
"from sklearn.metrics import confusion_matrix\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"from tensorflow.keras.models import Sequential\n",
"from tensorflow.keras.layers import Dense, Embedding, LSTM\n",
"from tensorflow.keras.preprocessing.text import Tokenizer\n",
"from tensorflow.keras.preprocessing.sequence import pad_sequences\n",
"\n",
"# Load and preprocess data\n",
"data = pd.read_csv('dataset.csv')\n",
"data['sentiment'] = data['sentiment'].apply(lambda x: 1 if x == 'positive' else 0)\n",
"train_data, test_data = train_test_split(data, test_size=0.2, random_state=42)\n",
"\n",
"# Tokenize and pad sequences for custom neural network model\n",
"tokenizer = Tokenizer()\n",
"tokenizer.fit_on_texts(train_data['statement'])\n",
"train_sequences = tokenizer.texts_to_sequences(train_data['statement'])\n",
"test_sequences = tokenizer.texts_to_sequences(test_data['statement'])\n",
"train_padded = pad_sequences(train_sequences, padding='post')\n",
"test_padded = pad_sequences(test_sequences, padding='post')\n",
"\n",
"# Train and evaluate Naive Bayes model using CountVectorizer\n",
"count_vectorizer = CountVectorizer()\n",
"X_train_count = count_vectorizer.fit_transform(train_data['statement'])\n",
"X_test_count = count_vectorizer.transform(test_data['statement'])\n",
"y_train = train_data['sentiment']\n",
"naive_bayes_count_model = MultinomialNB()\n",
"naive_bayes_count_model.fit(X_train_count, y_train)\n",
"naive_bayes_count_predictions = naive_bayes_count_model.predict(X_test_count)\n",
"\n",
"# Train and evaluate Naive Bayes model using TF-IDF\n",
"tfidf_vectorizer = TfidfVectorizer()\n",
"X_train_tfidf = tfidf_vectorizer.fit_transform(train_data['statement'])\n",
"X_test_tfidf = tfidf_vectorizer.transform(test_data['statement'])\n",
"naive_bayes_tfidf_model = MultinomialNB()\n",
"naive_bayes_tfidf_model.fit(X_train_tfidf, y_train)\n",
"naive_bayes_tfidf_predictions = naive_bayes_tfidf_model.predict(X_test_tfidf)\n",
"\n",
"# Train and evaluate SVM model using CountVectorizer\n",
"svm_count_model = SVC()\n",
"svm_count_model.fit(X_train_count, y_train)\n",
"svm_count_predictions = svm_count_model.predict(X_test_count)\n",
"\n",
"# Train and evaluate SVM model using TF-IDF\n",
"svm_tfidf_model = SVC()\n",
"svm_tfidf_model.fit(X_train_tfidf, y_train)\n",
"svm_tfidf_predictions = svm_tfidf_model.predict(X_test_tfidf)\n",
"\n",
"# Train and evaluate custom neural network model\n",
"model = Sequential()\n",
"model.add(Embedding(input_dim=len(tokenizer.word_index) + 1, output_dim=128, input_length=train_padded.shape[1]))\n",
"model.add(LSTM(64))\n",
"model.add(Dense(1, activation='sigmoid'))\n",
"model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])\n",
"model.fit(train_padded, train_data['sentiment'], epochs=10, validation_data=(test_padded, test_data['sentiment']))\n",
"custom_predictions = model.predict(test_padded)\n",
"custom_binary_predictions = (custom_predictions >= 0.5).astype(int)\n",
"\n",
"# Plot confusion matrices\n",
"def plot_confusion_matrix(matrix, title):\n",
" plt.figure(figsize=(8, 6))\n",
" sns.heatmap(matrix, annot=True, fmt=\"d\", cmap=\"Blues\", cbar=False)\n",
" plt.xlabel('Predicted Labels')\n",
" plt.ylabel('True Labels')\n",
" plt.title(title)\n",
" plt.show()\n",
"\n",
"# Confusion matrix for Naive Bayes model (CountVectorizer)\n",
"cm_nb_count = confusion_matrix(test_data['sentiment'], naive_bayes_count_predictions)\n",
"plot_confusion_matrix(cm_nb_count, 'Confusion Matrix - Naive Bayes (CountVectorizer)')\n",
"\n",
"# Confusion matrix for Naive Bayes model (TF-IDF)\n",
"cm_nb_tfidf = confusion_matrix(test_data['sentiment'], naive_bayes_tfidf_predictions)\n",
"plot_confusion_matrix(cm_nb_tfidf, 'Confusion Matrix - Naive Bayes (TF-IDF)')\n",
"\n",
"# Confusion matrix for SVM model (CountVectorizer)\n",
"cm_svm_count = confusion_matrix(test_data['sentiment'], svm_count_predictions)\n",
"plot_confusion_matrix(cm_svm_count, 'Confusion Matrix - SVM (CountVectorizer)')\n",
"\n",
"# Confusion matrix for SVM model (TF-IDF)\n",
"cm_svm_tfidf = confusion_matrix(test_data['sentiment'], svm_tfidf_predictions)\n",
"plot_confusion_matrix(cm_svm_tfidf, 'Confusion Matrix - SVM (TF-IDF)')\n",
"\n",
"# Confusion matrix for custom neural network model\n",
"cm_custom = confusion_matrix(test_data['sentiment'], custom_binary_predictions)\n",
"plot_confusion_matrix(cm_custom, 'Confusion Matrix - Custom Neural Network')\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "T1Nav262C2y2",
"outputId": "60d383da-b080-47a3-c963-7d6f14b87f6a"
},
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Epoch 1/10\n",
"34/34 [==============================] - 6s 37ms/step - loss: 0.5342 - accuracy: 0.7477 - val_loss: 0.1761 - val_accuracy: 0.9410\n",
"Epoch 2/10\n",
"34/34 [==============================] - 1s 20ms/step - loss: 0.1519 - accuracy: 0.9501 - val_loss: 0.1005 - val_accuracy: 0.9779\n",
"Epoch 3/10\n",
"34/34 [==============================] - 1s 20ms/step - loss: 0.0441 - accuracy: 0.9880 - val_loss: 0.1076 - val_accuracy: 0.9705\n",
"Epoch 4/10\n",
"34/34 [==============================] - 1s 21ms/step - loss: 0.0142 - accuracy: 0.9972 - val_loss: 0.1280 - val_accuracy: 0.9705\n",
"Epoch 5/10\n",
"34/34 [==============================] - 1s 19ms/step - loss: 0.0045 - accuracy: 0.9982 - val_loss: 0.1134 - val_accuracy: 0.9815\n",
"Epoch 6/10\n",
"34/34 [==============================] - 1s 32ms/step - loss: 0.0028 - accuracy: 0.9982 - val_loss: 0.1844 - val_accuracy: 0.9594\n",
"Epoch 7/10\n",
"34/34 [==============================] - 1s 35ms/step - loss: 7.1627e-04 - accuracy: 1.0000 - val_loss: 0.1882 - val_accuracy: 0.9594\n",
"Epoch 8/10\n",
"34/34 [==============================] - 1s 30ms/step - loss: 5.3644e-04 - accuracy: 1.0000 - val_loss: 0.1959 - val_accuracy: 0.9631\n",
"Epoch 9/10\n",
"34/34 [==============================] - 1s 20ms/step - loss: 4.3370e-04 - accuracy: 1.0000 - val_loss: 0.2032 - val_accuracy: 0.9631\n",
"Epoch 10/10\n",
"34/34 [==============================] - 1s 19ms/step - loss: 3.6074e-04 - accuracy: 1.0000 - val_loss: 0.2098 - val_accuracy: 0.9631\n",
"9/9 [==============================] - 0s 5ms/step\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 800x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 800x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 800x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 800x600 with 1 Axes>"
],
"image/png": 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g/vjjD5f1+/fv1/Tp0yX99Ta2JJdP7E+ZMkWSdM899+TbXJUrV1ZiYqJ27tzpWHbixAktXbrUabszZ8643Dfr4vjZfaOP9NfRvPr162v+/PlOQfzTTz9p9erVjudZEFq1aqXnn39eb7zxhlOQXc7b29vlqO0HH3ygY8eOOS3Liurswt5dI0aM0JEjRzR//nxNmTJFFStWdByZvJJmzZo5vcV8pVjdu3evjhw54rI8ISFBmzZtUmhoqMLCwpzWZR1FHTNmjGJjY696VDXL8OHDNXbsWI0ePTpX218q6xe3S79BKr/5+fm5vD2fdXqJuxYtWqTZs2erSZMmOZ7LezXbt2/XzTffrODg4DzdH/gn48gqYLDKlStr0aJFuu+++1SzZk2nb7DauHGjPvjgA8fXR9arV0/R0dF65513lJCQoKioKG3ZskXz589X586dc7wsUl706NFDI0aMUJcuXfT4448rOTlZb731lqpVq+b0AaMJEyZo/fr1uueeexQZGalTp07pzTffVLly5XTHHXfkuP9XXnlF7du3V5MmTfTAAw8oJSVFr7/+uoKDgzVu3Lh8ex6X8/Ly0nPPPXfV7Tp06KAJEyaof//+atq0qXbt2qWFCxe6hGDlypUVEhKimTNnqkSJEgoICFDjxo110003uTXXV199pTfffFNjx451XK5p7ty5atmypUaPHq1Jkya5tb+c7NixQ7169VL79u3VvHlzlSxZUseOHdP8+fN1/PhxTZs2zeWUi5tuuklNmzZ1XAM0t7Far169PB+prFSpkmrXrq0vv/xSAwYMyNM+CsqHH36owMBApaWlOb7B6rvvvlO9evX0wQcf5GmfFy9e1DfffKNHHnkkn6cF/hmIVcBwHTt21M6dO/XKK6/ok08+0VtvvSW73a66detq8uTJevDBBx3bzp49W5UqVdK8efO0dOlShYeHa+TIkRo7dmy+zlSqVCktXbpUMTExevrpp3XTTTdp4sSJ2rt3r1OsduzYUYcOHdKcOXMUFxen0qVLKyoqSuPHj7/iEaI2bdroiy++0NixYzVmzBj5+PgoKipKL7/8stuhVxCeffZZJSUladGiRXr//ffVsGFDrVy5Us8884zTdj4+Ppo/f75GjhypwYMHKz09XXPnznXrOZw7d04DBgxQgwYNNGrUKMfy5s2ba+jQoZo8ebK6du2q22+//ZqfV4sWLfT888/r888/15QpU3T69GmVKFFCDRo00Msvv6xu3bple7/evXtr48aNuu222/J8Tqa7BgwYoDFjxiglJcXtc38L0sMPPyzpryOzpUuXVv369TVnzhz16tVLdrs9T/tcu3atzpw5o+jo6PwcFfjHsFnufAIBAAADJCYmqlKlSpo0aZIeeOABT49ToDp37iybzeZymg1QVBCrAIB/pJdffllz587VL7/84rjubWGze/du1alTR7Gxsbn+OlqgsCFWAQAAYKzC+asoAAAACgViFQAAAMYiVgEAAGAsYhUAAADGIlYBAABgrEL5pQD+DR719AgAkK/iN7/u6REAIF8V97XlajuOrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxTw9AGCaZg0ra1jfNmpYq4IiwoLVfdg7Wr5up2P9qIfu1v+1bahy4aFKu5ihH3cf0bg3lmvrT4ed9tPujpv17KD2ql21rC6kpevb7XvVPWbW9X46AHBVS95frA/fX6zjx49JkipVrqJBg4fojuYtPDwZQKwCLgL87dr12zH995NNen/KIJf1+w6f0rCXP9DB3+Pkb/fRY33+peVvPqrancYr7ux5SVLn1vU1Y3RPjX1judZt+U3Finnp5soR1/upAECulClTRo898aQqREZKlqXlny7TsMeH6H8ffKzKVap6ejwUcTbLsixPD5Hf/Bs86ukRUEik/PiGy5HVy5UI8NOpb19V+4de07otv8nb20t7Vo7X8zM/0/xlm67jtCjM4je/7ukRUMRENWusJ558Sl26/tvTo6CQKu5ry9V2Hj2yGhcXpzlz5mjTpk06efKkJCk8PFxNmzZVv379FBYW5snxgKvyKeatB7o2U8K5ZO367a+3zxrUKK8by4QqM9PSpsUjVKZUkHb+9ruenbpMv+w/4eGJAeDKMjIytGb1F0pJSVbdevU9PQ7guVjdunWr2rZtq+LFi6tNmzaqVq2aJOmPP/7Qa6+9pv/85z9atWqVbrnllivuJzU1VampqU7LrMwM2by8C2x2oH3z2vrvf/qruJ+PTsb9qQ6D31B8QpIk6aZypSVJzw2+WyMmf6zDx+M19P7WWjVrqOp2nqCzfyZ7cnQAyNbe3/Youk9PpaWlyr94cU2e9oYqV67i6bEAz50GcPvtt6tevXqaOXOmbDbnw8CWZWnw4MHauXOnNm268tuo48aN0/jx452WeZe5VT4Rt+X7zCh6cjoNoLifr8LDglQ6JFD9uzZVy1urqcX9r+r02fO6r90tmjexn4Y8v1hzPv5OkuTrU0z7Vj2v8TNW6N2PvvPEU8E/HKcBoKBdvJimEydO6Py5c/pyzSot/fhDzZ67gGBFgcntaQAeu3TVjh07NGzYMJdQlSSbzaZhw4YpNjb2qvsZOXKkEhMTnX6KlWlUABMDf0u+kKYDR+O0ZdchPTx+kdIzMhXdpakk6URcoiTp1wN/v+WfdjFdh36PV/nwkh6ZFwCuxsfHVxUqRKrWzbX1+BNPqlq1Glr83n89PRbguVgNDw/Xli1bcly/ZcsWlSlT5qr7sdvtCgoKcvrhFABcb142m+w+f51V8+Puo7qQelFVK/7932+xYl6qULakjpw446kRAcAtlpWptLQ0T48BeO6c1eHDh2vQoEHavn27Wrdu7QjTP/74Q2vXrtWsWbP06quvemo8FGEB/r6qXP7vD/dVvLGU6la7UWf/TFZ8QpJGDGyrld/s0sm4RJUKCdRD3Vuo7A0h+njND5Kkc0kXNPvDbzV68N36/eRZHTlxRsOi20iSYxsAMMlr0yar2R0tFBERoaSkJH3+2Qpt27pFb86c7enRAM/F6pAhQ1S6dGlNnTpVb775pjIyMiRJ3t7eatSokebNm6fu3bt7ajwUYQ1rRWr17KGO25OGd5MkLfj0ez324v9UvWIZ9bm3sUqFBOhMYrK2/XxYbQZM1e4DJx33GTltqdIzMvXuC33lb/fR1p8Oq/2g15RwLuW6Px8AuJozZ85o9KgRijt9WoElSqhq1ep6c+Zs3d60madHA8y4zurFixcVFxcnSSpdurR8fHyuaX9cZxVAYcMHrAAUNv+I66xm8fHxUUQE3+4DAAAAZx77gBUAAABwNcQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACM5Xaszp8/XytXrnTcfvrppxUSEqKmTZvq8OHD+TocAAAAija3Y/Wll16Sv7+/JGnTpk2aMWOGJk2apNKlS2vYsGH5PiAAAACKrmLu3uHo0aOqUqWKJGnZsmXq1q2bBg0apGbNmqlly5b5PR8AAACKMLePrAYGBio+Pl6StHr1at15552SJD8/P6WkpOTvdAAAACjS3D6yeuedd2rgwIFq0KCBfvvtN919992SpJ9//lkVK1bM7/kAAABQhLl9ZHXGjBlq0qSJTp8+rY8++kilSpWSJG3fvl09e/bM9wEBAABQdNksy7I8PUR+82/wqKdHAIB8Fb/5dU+PAAD5qrivLVfb5eo0gJ07d+b6gevWrZvrbQEAAIAryVWs1q9fXzabTTkdhM1aZ7PZlJGRka8DAgAAoOjKVawePHiwoOcAAAAAXOQqViMjIwt6DgAAAMCF21cDkKQFCxaoWbNmKlu2rOMrVqdNm6ZPPvkkX4cDAABA0eZ2rL711luKiYnR3XffrYSEBMc5qiEhIZo2bVp+zwcAAIAizO1Yff311zVr1iyNGjVK3t7ejuW33HKLdu3ala/DAQAAoGhzO1YPHjyoBg0auCy32+1KSkrKl6EAAAAAKQ+xetNNNyk2NtZl+RdffKGaNWvmx0wAAACApFxeDeBSMTExGjJkiC5cuCDLsrRlyxYtXrxYEydO1OzZswtiRgAAABRRbsfqwIED5e/vr+eee07Jycnq1auXypYtq+nTp6tHjx4FMSMAAACKKJuV09dS5UJycrLOnz+vG264IT9numb+DR719AgAkK/iN7/u6REAIF8V97Xlaju3j6xmOXXqlPbs2SPpr69bDQsLy+uuAAAAgGy5/QGrc+fO6f7771fZsmUVFRWlqKgolS1bVn369FFiYmJBzAgAAIAiyu1YHThwoDZv3qyVK1cqISFBCQkJWrFihbZt26aHHnqoIGYEAABAEeX2OasBAQFatWqV7rjjDqflGzZsULt27Yy41irnrAIobDhnFUBhk9tzVt0+slqqVCkFBwe7LA8ODlZoaKi7uwMAAABy5HasPvfcc4qJidHJkycdy06ePKmnnnpKo0ePztfhAAAAULTl6moADRo0kM3296HavXv3qkKFCqpQoYIk6ciRI7Lb7Tp9+jTnrQIAACDf5CpWO3fuXMBjAAAAAK6u6UsBTMUHrAAUNnzACkBhU2AfsAIAAACuF7e/wSojI0NTp07VkiVLdOTIEaWlpTmtP3PmTL4NBwAAgKLN7SOr48eP15QpU3TfffcpMTFRMTEx6tq1q7y8vDRu3LgCGBEAAABFlduxunDhQs2aNUtPPvmkihUrpp49e2r27NkaM2aMvv/++4KYEQAAAEWU27F68uRJ1alTR5IUGBioxMRESVKHDh20cuXK/J0OAAAARZrbsVquXDmdOHFCklS5cmWtXr1akrR161bZ7fb8nQ4AAABFmtux2qVLF61du1aS9Nhjj2n06NGqWrWq+vbtqwEDBuT7gAAAACi6rvk6q99//702btyoqlWr6t57782vua4J11kFUNhwnVUAhc11u87q7bffrpiYGDVu3FgvvfTSte4OAAAAcMi3b7DasWOHGjZsqIyMjPzY3TW5kO7pCQAgf4W2eNbTIwBAvkrZmLuDnHyDFQAAAIxFrAIAAMBYxCoAAACMVSy3G8bExFxx/enTp695GAAAAOBSuY7VH3/88arbtGjR4pqGAQAAAC6V61j9+uuvC3IOAAAAwAXnrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFh5itUNGzaoT58+atKkiY4dOyZJWrBggb799tt8HQ4AAABFm9ux+tFHH6lt27by9/fXjz/+qNTUVElSYmKiXnrppXwfEAAAAEWX27H6wgsvaObMmZo1a5Z8fHwcy5s1a6YffvghX4cDAABA0eZ2rO7Zsyfbb6oKDg5WQkJCfswEAAAASMpDrIaHh2vfvn0uy7/99ltVqlQpX4YCAAAApDzE6oMPPqihQ4dq8+bNstlsOn78uBYuXKjhw4fr4YcfLogZAQAAUEQVc/cOzzzzjDIzM9W6dWslJyerRYsWstvtGj58uB577LGCmBEAAABFlM2yLCsvd0xLS9O+fft0/vx51apVS4GBgfk9W55dSPf0BACQv0JbPOvpEQAgX6VszN1VpNw+sprF19dXtWrVyuvdAQAAgKtyO1ZbtWolm82W4/qvvvrqmgYCAAAAsrgdq/Xr13e6ffHiRcXGxuqnn35SdHR0fs0FAAAAuB+rU6dOzXb5uHHjdP78+WseCAAAAMji9qWrctKnTx/NmTMnv3YHAAAA5F+sbtq0SX5+fvm1OwAAAMD90wC6du3qdNuyLJ04cULbtm3T6NGj820wAAAAwO1YDQ4Odrrt5eWl6tWra8KECbrrrrvybTAAAADArVjNyMhQ//79VadOHYWGhhbUTAAAAIAkN89Z9fb21l133aWEhIQCGgcAAAD4m9sfsKpdu7YOHDhQELMAAAAATtyO1RdeeEHDhw/XihUrdOLECf35559OPwAAAEB+sVmWZeVmwwkTJujJJ59UiRIl/r7zJV+7almWbDabMjIy8n9KN11I9/QEAJC/Qls86+kRACBfpWx8KVfb5TpWvb29deLECe3evfuK20VFReXqgQsSsQqgsCFWARQ2uY3VXF8NIKtpTYhRAAAAFA1unbN66dv+AAAAQEFz6zqr1apVu2qwnjlz5poGAgAAALK4Favjx493+QYrAAAAoKC4Fas9evTQDTfcUFCzAAAAAE5yfc4q56sCAADgest1rObyClcAAABAvsn1aQCZmZkFOQcAAADgwu2vWwUAAACuF2IVAAAAxiJWAQAAYCxiFQAAAMYiVgEAAGAsYhUAAADGIlYBAABgLGIVAAAAxiJWAQAAYCxiFQAAAMYiVgEAAGAsYhUAAADGIlYBAABgLGIVAAAAxiJWAQAAYCxiFQAAAMYiVgEAAGAsYhUAAADGIlYBAABgLGIVAAAAxiJWAQAAYCxiFQAAAMYiVgEAAGAsYhUAAADGIlYBAABgLGIVAAAAxiJWAQAAYCxiFQAAAMYiVgEAAGAsYhUAAADGIlYBAABgLGIVAAAAxiJWAQAAYCxiFQAAAMYiVgEAAGAsYhUAAADGIlYBAABgLGIVAAAAxiJWAQAAYCxiFQAAAMYiVgEAAGAsYhUAAADGIlYBAABgLGIVAAAAxiJWAQAAYCxiFQAAAMYiVgEAAGAsYhUAAADGIlYBAABgLGIVAAAAxiJWAQAAYCxiFQAAAMYiVgEAAGAsYhUAAADGIlYBAABgLGIVAAAAxiJWAQAAYCxiFQAAAMYiVgEAAGAsYhUAAADGIlYBAABgLGIVAAAAxiJWAQAAYCxiFQAAAMYiVgEAAGAsYhUAAADGIlYBAABgLGIVAAAAxirm6QGAf5rt27Zq3px3tfuXn3T69GlNfW2G/tW6jafHAoAcNatfUcN6NVfD6jcqIixI3Z9ZoOXrdzvWj3qgtf6vTV2VuyFYaRcz9OOeYxr39mpt/eV3xzZPR7dU+6bVVbdqhNIuZiii7fOeeCoogjiyCrgpJSVZ1atX18jnxnp6FADIlQA/X+3ad1JPTP402/X7jsRp2ORPdcv909X64bd1+MRZLZ82QKVDAhzb+Bbz1sdf/aRZSzdfr7EBSRxZBdx2R/Mo3dE8ytNjAECurf7+N63+/rcc17+/ZofT7RGvfab+HW9V7crhWrd9vyTphXfXSpL63N2w4AYFssGRVQAA4OBTzFsPdLpVCedStGvfCU+PA5h9ZPXo0aMaO3as5syZk+M2qampSk1NdVpmedtlt9sLejwAAAqN9k2r678Teqi4n49Oxp9ThyfmKD4x2dNjAWYfWT1z5ozmz59/xW0mTpyo4OBgp59XXp54nSYEAKBw+OaHA2oc/bpaPfS2Vn+/V+8931NhoQFXvyNQwDx6ZPXTT7M/0TvLgQMHrrqPkSNHKiYmxmmZ5c1RVQAA3JF84aIOHDujA8fOaMvPR7Xr/RhFd7hFry74xtOjoYjzaKx27txZNptNlmXluI3NZrviPux217f8L6Tny3gAABRZXl422X2NPlsQRYRH/yuMiIjQm2++qU6dOmW7PjY2Vo0aNbrOUwFXlpyUpCNHjjhuH/v9d/26e7eCg4MVUbasBycDgOwF+PuqcrlSjtsVI0qqbtUInf0zWfGJyRoR3Uorv92tk/HnVCq4uB7qdrvKlg7Sx1/tctynfJlghQYVV/kyIfL28lLdqhGSpP2/xyspJe26PycUHR6N1UaNGmn79u05xurVjroCnvDzzz9pYP++jtuvTvrrHOmOnbro+Zf+46mxACBHDWvcqNUzHnTcnjT0HknSgpXb9dgrn6h6ZJj63N1ApYIDdCYxWdt+/V1tHnlHuw+ectxn9MA2uv+evw8gbZ7/mCTpriGztOHHg9fpmaAoslkerMENGzYoKSlJ7dq1y3Z9UlKStm3bpqgo965pyWkAAAqb0BbPenoEAMhXKRtfytV2Hj2y2rx58yuuDwgIcDtUAQAAUHgYfekqAAAAFG3EKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKgAAAIxFrAIAAMBYxCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFg2y7IsTw8B/BOlpqZq4sSJGjlypOx2u6fHAYBrxp9rMBGxCuTRn3/+qeDgYCUmJiooKMjT4wDANePPNZiI0wAAAABgLGIVAAAAxiJWAQAAYCxiFcgju92usWPH8iEEAIUGf67BRHzACgAAAMbiyCoAAACMRawCAADAWMQqAAAAjEWsAgAAwFjEKpBHM2bMUMWKFeXn56fGjRtry5Ytnh4JAPJk/fr1uvfee1W2bFnZbDYtW7bM0yMBDsQqkAfvv/++YmJiNHbsWP3www+qV6+e2rZtq1OnTnl6NABwW1JSkurVq6cZM2Z4ehTABZeuAvKgcePGuvXWW/XGG29IkjIzM1W+fHk99thjeuaZZzw8HQDknc1m09KlS9W5c2dPjwJI4sgq4La0tDRt375dbdq0cSzz8vJSmzZttGnTJg9OBgBA4UOsAm6Ki4tTRkaGypQp47S8TJkyOnnypIemAgCgcCJWAQAAYCxiFXBT6dKl5e3trT/++MNp+R9//KHw8HAPTQUAQOFErAJu8vX1VaNGjbR27VrHsszMTK1du1ZNmjTx4GQAABQ+xTw9APBPFBMTo+joaN1yyy267bbbNG3aNCUlJal///6eHg0A3Hb+/Hnt27fPcfvgwYOKjY1VyZIlVaFCBQ9OBnDpKiDP3njjDb3yyis6efKk6tevr9dee02NGzf29FgA4LZ169apVatWLsujo6M1b9686z8QcAliFQAAAMbinFUAAAAYi1gFAACAsYhVAAAAGItYBQAAgLGIVQAAABiLWAUAAICxiFUAAAAYi1gFAACAsYhVAHBTv3791LlzZ8ftli1b6oknnrjuc6xbt042m00JCQkF9hiXP9e8uB5zAii8iFUAhUK/fv1ks9lks9nk6+urKlWqaMKECUpPTy/wx/7444/1/PPP52rb6x1uFStW1LRp067LYwFAQSjm6QEAIL+0a9dOc+fOVWpqqj777DMNGTJEPj4+GjlypMu2aWlp8vX1zZfHLVmyZL7sBwDgiiOrAAoNu92u8PBwRUZG6uGHH1abNm306aefSvr77ewXX3xRZcuWVfXq1SVJR48eVffu3RUSEqKSJUuqU6dOOnTokGOfGRkZiomJUUhIiEqVKqWnn35almU5Pe7lpwGkpqZqxIgRKl++vOx2u6pUqaJ3331Xhw4dUqtWrSRJoaGhstls6tevnyQpMzNTEydO1E033SR/f3/Vq1dPH374odPjfPbZZ6pWrZr8/f3VqlUrpznzIiMjQw888IDjMatXr67p06dnu+348eMVFhamoKAgDR48WGlpaY51uZn9UocPH9a9996r0NBQBQQE6Oabb9Znn312Tc8FQOHFkVUAhZa/v7/i4+Mdt9euXaugoCCtWbNGknTx4kW1bdtWTZo00YYNG1SsWDG98MILateunXbu3ClfX19NnjxZ8+bN05w5c1SzZk1NnjxZS5cu1b/+9a8cH7dv377atGmTXnvtNdWrV08HDx5UXFycypcvr48++kjdunXTnj17FBQUJH9/f0nSxIkT9d5772nmzJmqWrWq1q9frz59+igsLExRUVE6evSounbtqiFDhmjQoEHatm2bnnzyyWt6fTIzM1WuXDl98MEHKlWqlDZu3KhBgwYpIiJC3bt3d3rd/Pz8tG7dOh06dEj9+/dXqVKl9OKLL+Zq9ssNGTJEaWlpWr9+vQICAvTLL78oMDDwmp4LgELMAoBCIDo62urUqZNlWZaVmZlprVmzxrLb7dbw4cMd68uUKWOlpqY67rNgwQKrevXqVmZmpmNZamqq5e/vb61atcqyLMuKiIiwJk2a5Fh/8eJFq1y5co7HsizLioqKsoYOHWpZlmXt2bPHkmStWbMm2zm//vprS5J19uxZx7ILFy5YxYsXtzZu3Oi07QMPPGD17NnTsizLGjlypFWrVi2n9SNGjHDZ1+UiIyOtqVOn5rj+ckOGDLG6devmuB0dHW2VLFnSSkpKcix76623rMDAQCsjIyNXs1/+nOvUqWONGzcu1zMBKNo4sgqg0FixYoUCAwN18eJFZWZmqlevXho3bpxjfZ06dZzOU92xY4f27dunEiVKOO3nwoUL2r9/vxITE3XixAk1btzYsa5YsWK65ZZbXE4FyBIbGytvb+9sjyjmZN++fUpOTtadd97ptDwtLU0NGjSQJO3evdtpDklq0qRJrh8jJzNmzNCcOXN05MgRpaSkKC0tTfXr13fapl69eipevLjT454/f15Hjx7V+fPnrzr75R5//HE9/PDDWr16tdq0aaNu3bqpbt261/xcABROxCqAQqNVq1Z666235Ovrq7Jly6pYMec/4gICApxunz9/Xo0aNdLChQtd9hUWFpanGbLe1nfH+fPnJUkrV67UjTfe6LTObrfnaY7c+N///qfhw4dr8uTJatKkiUqUKKFXXnlFmzdvzvU+8jL7wIED1bZtW61cuVKrV6/WxIkTNXnyZD322GN5fzIACi1iFUChERAQoCpVquR6+4YNG+r999/XDTfcoKCgoGy3iYiI0ObNm9WiRQtJUnp6urZv366GDRtmu32dOnWUmZmpb775Rm3atHFZn3VkNyMjw7GsVq1astvtOnLkSI5HZGvWrOn4sFiW77///upP8gq+++47NW3aVI888ohj2f79+12227Fjh1JSUhwh/v333yswMFDly5dXyZIlrzp7dsqXL6/Bgwdr8ODBGjlypGbNmkWsAsgWVwMAUGT17t1bpUuXVqdOnbRhwwYdPHhQ69at0+OPP67ff/9dkjR06FD95z//0bJly/Trr7/qkUceueI1UitWrKjo6GgNGDBAy5Ytc+xzyZIlkqTIyEjZbDatWLFCp0+f1vnz51WiRAkNHz5cw4YN0/z587V//3798MMPev311zV//nxJ0uDBg7V371499dRT2rNnjxYtWqR58+bl6nkeO3ZMsbGxTj9nz55V1apVtW3bNq1atUq//fabRo8era1bt7rcPy0tTQ888IB++eUXffbZZxo7dqweffRReXl55Wr2yz3xxBNatWqVDh48qB9++EFff/21atasmavnAqAI8vRJswCQHy79gJU760+cOGH17dvXKl26tGW3261KlSpZDz74oJWYmGhZ1l8fqBo6dKgVFBRkhYSEWDExMVbfvn1z/ICVZVlWSkqKNWzYMCsiIsLy9fW1qlSpYs2ZM8exfsKECVZ4eLhls9ms6Ohoy7L++lDYtGnTrOrVq1s+Pj5WWFiY1bZtW+ubb75x3G/58uVWlSpVLLvdbjVv3tyaM2dOrj5gJcnlZ8GCBdaFCxesfv36WcHBwVZISIj18MMPW88884xVr149l9dtzJgxVqlSpazAwEDrwQcftC5cuODY5mqzX/4Bq0cffdSqXLmyZbfbrbCwMOv++++34uLicnwOAIo2m2Xl8CkBAAAAwMM4DQAAAADGIlYBAABgLGIVAAAAxiJWAQAAYCxiFQAAAMYiVgEAAGAsYhUAAADGIlYBAABgLGIVAAAAxiJWAQAAYCxiFQAAAMb6fwVfXxBk8nAvAAAAAElFTkSuQmCC\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 800x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"import matplotlib.pyplot as plt\n",
"from sklearn.metrics import roc_curve, auc\n",
"\n",
"# Calculate ROC curve for Naive Bayes (CountVectorizer)\n",
"fpr_nb_cv, tpr_nb_cv, _ = roc_curve(test_data['sentiment'], naive_bayes_count_predictions)\n",
"roc_auc_nb_cv = auc(fpr_nb_cv, tpr_nb_cv)\n",
"\n",
"# Plot ROC curve\n",
"plt.figure()\n",
"plt.plot(fpr_nb_cv, tpr_nb_cv, color='darkorange', lw=2, label='Naive Bayes (CountVectorizer) (area = %0.2f)' % roc_auc_nb_cv)\n",
"plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')\n",
"plt.xlim([0.0, 1.0])\n",
"plt.ylim([0.0, 1.05])\n",
"plt.xlabel('False Positive Rate')\n",
"plt.ylabel('True Positive Rate')\n",
"plt.title('ROC Curve - Naive Bayes (CountVectorizer)')\n",
"plt.legend(loc='lower right')\n",
"plt.show()\n",
"\n",
"\n",
"# Calculate ROC curve for SVM (CountVectorizer)\n",
"fpr_svm_cv, tpr_svm_cv, _ = roc_curve(test_data['sentiment'], svm_count_predictions)\n",
"roc_auc_svm_cv = auc(fpr_svm_cv, tpr_svm_cv)\n",
"\n",
"# Plot ROC curve\n",
"plt.figure()\n",
"plt.plot(fpr_svm_cv, tpr_svm_cv, color='darkorange', lw=2, label='SVM (CountVectorizer) (area = %0.2f)' % roc_auc_svm_cv)\n",
"plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')\n",
"plt.xlim([0.0, 1.0])\n",
"plt.ylim([0.0, 1.05])\n",
"plt.xlabel('False Positive Rate')\n",
"plt.ylabel('True Positive Rate')\n",
"plt.title('ROC Curve - SVM (CountVectorizer)')\n",
"plt.legend(loc='lower right')\n",
"plt.show()\n",
"\n",
"\n",
"\n",
"# Calculate ROC curve for Naive Bayes (TF-IDF)\n",
"fpr_nb_tfidf, tpr_nb_tfidf, _ = roc_curve(test_data['sentiment'], naive_bayes_tfidf_predictions)\n",
"roc_auc_nb_tfidf = auc(fpr_nb_tfidf, tpr_nb_tfidf)\n",
"\n",
"# Plot ROC curve\n",
"plt.figure()\n",
"plt.plot(fpr_nb_tfidf, tpr_nb_tfidf, color='darkorange', lw=2, label='Naive Bayes (TF-IDF) (area = %0.2f)' % roc_auc_nb_tfidf)\n",
"plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')\n",
"plt.xlim([0.0, 1.0])\n",
"plt.ylim([0.0, 1.05])\n",
"plt.xlabel('False Positive Rate')\n",
"plt.ylabel('True Positive Rate')\n",
"plt.title('ROC Curve - Naive Bayes (TF-IDF)')\n",
"plt.legend(loc='lower right')\n",
"plt.show()\n",
"\n",
"\n",
"\n",
"# Calculate ROC curve for SVM (TF-IDF)\n",
"fpr_svm_tfidf, tpr_svm_tfidf, _ = roc_curve(test_data['sentiment'], svm_tfidf_predictions)\n",
"roc_auc_svm_tfidf = auc(fpr_svm_tfidf, tpr_svm_tfidf)\n",
"\n",
"# Plot ROC curve\n",
"plt.figure()\n",
"plt.plot(fpr_svm_tfidf, tpr_svm_tfidf, color='darkorange', lw=2, label='SVM (TF-IDF) (area = %0.2f)' % roc_auc_svm_tfidf)\n",
"plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')\n",
"plt.xlim([0.0, 1.0])\n",
"plt.ylim([0.0, 1.05])\n",
"plt.xlabel('False Positive Rate')\n",
"plt.ylabel('True Positive Rate')\n",
"plt.title('ROC Curve - SVM (TF-IDF)')\n",
"plt.legend(loc='lower right')\n",
"plt.show()\n",
"\n",
"\n",
"\n",
"# Calculate ROC curve for the custom model\n",
"custom_pred_probs = model.predict(test_padded)\n",
"fpr_custom, tpr_custom, _ = roc_curve(test_data['sentiment'], custom_pred_probs)\n",
"roc_auc_custom = auc(fpr_custom, tpr_custom)\n",
"\n",
"# Plot ROC curve\n",
"plt.figure()\n",
"plt.plot(fpr_custom, tpr_custom, color='darkorange', lw=2, label='Custom Model (area = %0.2f)' % roc_auc_custom)\n",
"plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')\n",
"plt.xlim([0.0, 1.0])\n",
"plt.ylim([0.0, 1.05])\n",
"plt.xlabel('False Positive Rate')\n",
"plt.ylabel('True Positive Rate')\n",
"plt.title('ROC Curve - Custom Model')\n",
"plt.legend(loc='lower right')\n",
"plt.show()\n",
"\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "kBLsseg_d116",
"outputId": "d91592fe-a8af-45f6-aa23-f242d9bc98c1"
},
"execution_count": 7,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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Xr8XixYtF48aNhZmZmVAqlaJKlSpi3Lhx4u7duxp1t2/fLipVqiSUSqWoX7++8Pf3F4MHDxYVKlSQ6mR0F+L3xcbGChMTEwFAbN++PcM6r169ElOnThWVK1cWSqVSWFtbCxcXF7F48WKRnJycrdf2ISkpKWL9+vXCw8NDVKhQQRgZGQlTU1PRoEEDsWjRokzvhn3z5k0BQBgZGYno6OgM66TdWTorWd2d+X2XLl0SAMTp06czrSPHnaXTHoaGhqJUqVKiVatWYt68eeLp06fpjpPdO0u/fPlSKJVKsWHDBq1jJcpLCiFyYcoCERHlSPv27VGmTJl0a4wVNcuWLcPChQtx7969TAfdE8mBiRARkYzOnz+Pli1b4t9//0WFChXkDidPpKSkwNHREd7e3vj888/lDodIAxMhIiIi0lmcNUZEREQ6i4kQERER6SwmQkRERKSzmAgRERGRztK5Gyqq1Wo8efIE5ubmBeoGZkRERJQ5IQRevXqFMmXKQE8v99pxdC4RevLkCezt7eUOg4iIiHLg4cOH2VoCJ7t0LhEyNzcH8OaNtLCwkDkaIiIiyo7Y2FjY29tL3+O5RecSobTuMAsLCyZCREREhUxuD2vhYGkiIiLSWUyEiIiISGcxESIiIiKdxUSIiIiIdBYTISIiItJZTISIiIhIZzERIiIiIp3FRIiIiIh0FhMhIiIi0llMhIiIiEhnyZoI/fXXX+jatSvKlCkDhUKBAwcOfHCfgIAAODk5wcjICJUrV4aPj0+ex0lERERFk6yJUHx8POrVq4eVK1dmq/79+/fRuXNntG3bFleuXMGECRMwYsQI+Pv753GkREREVBTJuujqJ598gk8++STb9desWYOKFStiyZIlAIAaNWrgzJkz+PHHH+Hm5pZXYRIREVERVahWnw8MDISrq6tGmZubGyZMmCBPQEREVHAIAQg1gP//V4i3P2dU9m79jMqEAPB+WTaPiyzOleFx3zteRmUfOm5m5/rQcTM9VwZlufIatH8/1So1bgbnza9NoUqEIiIiULp0aY2y0qVLIzY2FgkJCTAxMUm3T1JSEpKSkqTnsbGxeR4nUYGXkw+93PwwzfYXRh4dN9uvMa++THPhi0iu61RQfyeoyAqPNcPQXR44dc82T45fqBKhnFiwYAHmzJmTs52l/4gf+2GaCx96eZV959UXUUH66+ujrpO271cuf2HkxRcsEVEhcfBGNYzY0w1R8cUAJObJOQpVImRra4vIyEiNssjISFhYWGTYGgQAU6dOxaRJk6TnsbGxsLe3//DJEp4De1yBZ1c+JmQioiJEASgU//+v3pufFXpvnmdUplAAyKBM+jmTsnf3y5dzZVD2oXN96LjanCu7rzunx83sXFq/n7nxGrJ/nZ49T0b/WQcQH58KALApZYKnz3LnN/ldhSoRcnZ2xpEjRzTK/vjjDzg7O2e6j5GREYyMjLQ/2b/7mQTRR8jiCyM/Pzhz88M0p19O6c6bvx+mheJLryD8TmTruET5p5QVsGxZEkaO/A0eHtWxdGlrVKo0K9fPI2siFBcXh7t370rP79+/jytXrqBEiRIoX748pk6disePH2Pr1q0AgNGjR+Pnn3/G//73PwwbNgx//vkndu/ejcOHD+d+cMmxb3+2qgaYlkK2P0zz6gMuP/+CyO8vPa3/Msnua8zHL1N+YRAR5ZhKpUZqqhpGRm9Tk+HDG8De3gIdOzri1atXeXJeWROhixcvom3bttLztC6swYMHw8fHB+Hh4Xjw4IG0vWLFijh8+DAmTpyI5cuXo1y5ctiwYUPeTJ1XvR1gjVYLgcrdcv8cREREhIcPYzBo0AHUrl0KP/3USSpXKBRwc6ucp+eWNRFq06YNhBCZbs/ortFt2rTB5cuX8zCq/5f6zqAsA+O8Px8REZEO2r37JkaNOoSXLxMREBCGTz6pgk6dquTb+QvVGKF8pWIiRERElFdiY5MwfvxRbNlyVSqzt7eAubkyX+NgIpSZd1uE9JkIERER5ZbAwIcYMGA/QkOjpTJPz1pYvbozrKwyngWeV5gIZYYtQkRERLkqNVWNefP+wnff/QWV6s3QGHNzJVau7IQBA+pCIcNkEyZCmdFoEcrB9HsiIiKSPH/+Gl27/oLAwEdSmYuLPbZv74GKFa1ki0tPtjMXdBwsTURElGuKFzeGgcGbtENfX4E5c9rg1KkhsiZBABOhzL07fZ5jhIiIiD6Kvr4etm3rAScnO5w5MwwzZ7aWEiM5sWssMxwjRERElGOnToXBxMQQTZqUlcoqVCiOixdHyjIWKDPyp2IFFWeNERERaS05WYWpU4+jbdst6NfvV7x6laSxvSAlQQATocy92yKkn7/3NCAiIiqMgoOj4Oy8Ed9/fxZCAKGh0Vi9+qLcYWWJXWOZSWsR0jfi2lFERERZEEJg/fpLmDDhGBIS3qwWb2ioh3nz2mHyZBeZo8saE6HMpCVCHB9ERESUqWfP4jFy5G84eDBYKqtWrSR8fXvByclOxsiyh4lQZtJmjXF8EBERUYb8/e9iyJCDiIiIk8pGj26IJUvcYGpqKGNk2cdEKDMqtggRERFlJjIyDh4eu5CY+KYrzNraFJs2dUPXrtVkjkw7HCydGWmMEBMhIiKi95UubYbvv28PAHBzc8T162MKXRIEsEUoc2wRIiIikqjVAiqVGoaG+lLZuHFNUa6cBXr0qAE9vcI5sYgtQhkRQnPWGBERkQ4LD3+FTz7ZgenT/9Qo19NToFevmoU2CQKYCGVMlfz2Z7YIERGRDjt48A7q1FmN33+/h0WLzuHPP+/LHVKuYtdYRlS8qzQREem2+PhkTJ78O9auDZLKSpc2kzGivMFEKCPvLrjKFiEiItIxQUFP4OW1DyEhz6Wy7t2rYcOGbrC2NpUxstzHRCgjXGeMiIh0kEqlxuLF5zB9+kmkpqoBAKamhli2zA0jRjgVuHXCcgMToYykcuV5IiLSLVFRr9G79x4EBIRJZQ0b2sHXtxeqVi0pX2B5jIOlM6JiIkRERLrF0tIIcXFvJgspFMDUqS1w7tzwIp0EAUyEMqbRNcbp80REVPQZGupjx46eqFHDGidPDsb8+e2hVOp/eMdCjl1jGeGsMSIiKuICAx/C1NQQ9erZSmVVq5bEjRufF+r7AmmLLUIZSeWsMSIiKppSU9WYMycALVtuRr9+v+L16xSN7bqUBAFMhDLGMUJERFQEhYZGo1WrzZg9+xRUKoHbt6OwatU/coclK3aNZYTT54mIqAgRQmDbtmsYO/YIXr16MyBaX1+BWbNaY8KEZjJHJy8mQhlhixARERUR0dEJGD36MHbvvimVOTpaYfv2nmjWrJyMkRUMTIQywlljRERUBAQEhGHgwP149ChWKhs6tD6WL3eHuTm/3wAmQhnjDRWJiKiQCw9/BTe37UhOVgEArKyMsXZtF/TuXUvmyAoWDpbOyLtrjXGMEBERFUJ2duaYNas1AKBtWwdcuzaGSVAG2CKUEY4RIiKiQkYIAbVaQF//bRvH1183h729Bfr3r6tz0+Kziy1CGeGsMSIiKkSePYtHjx67MHfuXxrl+vp6GDiwHpOgLLBFKCMcI0RERIWEv/9dDBlyEBERcTh0KAQdOzrC2dle7rAKDSZCGVFx1hgRERVsiYmpmDr1OJYtOy+VWVmZSPcJouxhIpQRtggREVEBdv16JPr334fr159KZW5ujvDx8YCtrZmMkRU+TIQywkVXiYioAFKrBX766Ty+/vo4kpLeTIs3MtLHwoUdMHZsE44FygEmQhlRcdFVIiIqWJ4/f43+/ffB3/+eVFanjg18fXuhdm0bGSMr3DhrLCOcNUZERAVMsWJKPH78Sno+cWIzXLgwkknQR2IilBGOESIiogLG2NgAvr49UbFicfj7D8DSpW4wNmbHzsfiO5gR3lCRiIhkFhT0BMWKKVG9urVUVqdOaYSEjIOBAdsxcgvfyYyktQgp9AA95opERJR/VCo1fvjhDJo124h+/X5FUlKqxnYmQbmL72ZG0lqEOD6IiIjy0cOHMWjffiu8vU8gNVWNK1cisGrVP3KHVaSxuSMjabPG2C1GRET5ZPfumxg16hBevnzzx7hCAXh7t8AXXzSRObKijYlQRtK6xpgIERFRHouNTcL48UexZctVqcze3gLbtvVA69YO8gWmI5gIZSSVXWNERJT3AgMfYsCA/QgNjZbKPD1rYfXqzrCyMpExMt3BRCgjKrYIERFR3nr8OBZt2mxBcvKbO0SbmyuxcmUnDBhQFwoF7xCdXzhYOiNSixAXXCUiorxRtqwFpkxxBgC4uNjj6tXRGDiwHpOgfMYWofepVYA65c3P7BojIqJcIoQAAI1EZ/bsNihf3hLDhztxWrxM+K6/j+uMERFRLouOTkDfvr9iyZJAjXJDQ32MGtWISZCM2CL0PiZCRESUiwICwjBw4H48ehSL/ftvo337imjQwE7usOj/MQV9HxdcJSKiXJCcrIK393G0a7cFjx7FAgDMzJSIiIiTOTJ6F1uE3sd1xoiI6CMFB0fBy2sfLl0Kl8ratnXA1q09UK6chYyR0fuYCL1Po0WIs8aIiCj7hBBYty4IEyf6IyHhzRphhoZ6mDevHSZPdoGeHmeEFTRMhN6XyhYhIiLS3osXCRg69CD8/IKlsmrVSsLXtxecnDgmqKBiIvQ+FccIERGR9oyM9HHnTpT0fMyYRli8uCNMTQ1ljIo+hIOl38dZY0RElAPFiimxY0dPlCljDj+/vli1qjOToEKALULv46wxIiLKhuvXI1GsmBKVKllJZY0alUFo6HgYGfHrtbBgi9D7OEaIiIiyoFYLLF/+Nxo3Xo/+/fchNVWtsZ1JUOHCROh9nD5PRESZCA9/hU8+2YEJE/yRlKTC338/wurV/8gdFn0E2ROhlStXwsHBAcbGxmjatCkuXLiQZf1ly5ahWrVqMDExgb29PSZOnIjExMQs99EKp88TEVEGDh68gzp1VuP33+9JZRMnNsPIkQ1ljIo+lqztd7t27cKkSZOwZs0aNG3aFMuWLYObmxuCg4NhY2OTrr6vry+8vb2xadMmuLi4ICQkBEOGDIFCocDSpUtzJyjOGiMionfExydj8uTfsXZtkFRmZ2cGHx8PdOzoKGNklBtkbRFaunQpRo4ciaFDh6JmzZpYs2YNTE1NsWnTpgzrnzt3Ds2bN4eXlxccHBzQsWNH9OvX74OtSFrhrDEiIvp/QUFP4OS0TiMJ8vCojmvXxjAJKiJkS4SSk5MRFBQEV1fXt8Ho6cHV1RWBgYEZ7uPi4oKgoCAp8QkNDcWRI0fQqVOnTM+TlJSE2NhYjUeWOGuMiIgAPHwYAxeXTQgJeQ4AMDU1xPr1XbFvXx9YW5vKHB3lFtkSoaioKKhUKpQuXVqjvHTp0oiIiMhwHy8vL3z77bdo0aIFDA0N4ejoiDZt2uCbb77J9DwLFiyApaWl9LC3t886MM4aIyIiAPb2lvj880YAgIYN7XD58iiMGOEEhYLLZBQlsg+W1kZAQADmz5+PVatW4dKlS9i3bx8OHz6M7777LtN9pk6dipiYGOnx8OHDrE/CWWNERDpLCKHxfMECVyxd2hHnzg1H1aolZYqK8pJsg6Wtra2hr6+PyMhIjfLIyEjY2tpmuM+MGTMwcOBAjBgxAgBQp04dxMfH47PPPsO0adOgp5c+rzMyMoKRkRazvzhrjIhI58TGJmH8+KNo0qQsPv+8sVRubGyAiROdZYyM8ppsLUJKpRINGzbEiRMnpDK1Wo0TJ07A2TnjX7rXr1+nS3b09fUBpM/ic4yzxoiIdEpg4EPUr78GW7ZcxeTJv+P27Wdyh0T5SNbp85MmTcLgwYPRqFEjNGnSBMuWLUN8fDyGDh0KABg0aBDKli2LBQsWAAC6du2KpUuXokGDBmjatCnu3r2LGTNmoGvXrlJC9NE4RoiISCekpqoxd+5fmDv3L6hUb/6YNjTUw7170ahRo5TM0VF+kTUR8vT0xLNnzzBz5kxERESgfv36OHbsmDSA+sGDBxotQNOnT4dCocD06dPx+PFjlCpVCl27dsW8efNyLyhOnyciKvJCQ6MxYMA+BAY+kspcXOyxfXsPVKxolcWeVNQoRK71KRUOsbGxsLS0RExMDCwsLNJXONgTuLv/zc+jngBmdvkbIBER5RkhBLZuvYqxY48iLi4ZAKCvr8DMma3xzTctYWBQqOYQ6ZQPfn/nEFeGex9njRERFUkvXyZi1KhD2L37plRWqZIVduzoiWbNyskYGcmJidD7OGuMiKhIUiiA8+ffdoUNGVIfK1a4w9ycn/W6jG2A72MiRERUJFlaGmPbth6wtjbF7t2fYvPm7kyCiC1C6aR1jekZAnq5NBONiIjyXXBwFIoVU6JcubfjSVq2rICwsC9RrJhSxsioIGGL0PvSZo1xfBARUaEkhMDatRfRoMFaDBq0H2q15pwgJkH0LiZC70vrGuPNFImICp1nz+Lh4bELo0cfRkJCKk6eDMO6dUEf3pF0FrvG3pfWNcYWISKiQsXf/y6GDDmIiIg4qWz06IYYNKiejFFRQcdE6H2pTISIiAqTxMRUTJ16HMuWnZfKrK1NsWlTN3TtWk3GyKgwYCL0PqlrjDMJiIgKuuvXI9G//z5cv/5UKnNzc4SPjwdsbc1kjIwKCyZC7xLibdcYxwgRERVo//33Eo0br0dSkgoAYGSkj4ULO2Ds2CbQ01PIHB0VFhws/S51KiDUb35m1xgRUYFWoUJxafxPnTo2uHjxM4wf35RJEGmFLULvenfBVbYIEREVeD/+6IYKFSwxebILjI35lUbaY4vQu1K5zhgRUUEUH5+M0aMPwcfnikZ5sWJKTJvWikkQ5Rh/c97FBVeJiAqcoKAn6N9/H4KDn2PHjuto2bI8HB1LyB0WFRFsEXoX1xkjIiowVCo1fvjhDJo124jg4OcAALVa4MaNpx/Ykyj72CL0rndbhDhGiIhINg8fxmDgwP04deo/qaxhQzv4+vZC1aolZYyMihomQu/iGCEiItnt3n0To0YdwsuXbz6TFQrA27sFZs9uA6WSi2FT7mIi9C7OGiMiks2rV0kYN+4otmy5KpXZ21tg27YeaN3aQb7AqEhjIvQutggREckmKUmF33+/Jz339KyF1as7w8rKRMaoqKjjYOl3cdYYEZFsrK1NsWWLBywsjLB1qwd++aUXkyDKc2wRelcqB0sTEeWX0NBoFCtmiNKl364J1qGDI/77bwKKF+dnMOUPtgi9S8Xp80REeU0IgS1brqBevTUYNswPQgiN7UyCKD8xEXoXxwgREeWp6OgE9O37K4YMOYi4uGQcOfIvNm++IndYpMPYNfYuJkJERHkmICAMAwfux6NHsVLZkCH10bt3TRmjIl3HROhdnD5PRJTrkpNVmDnzJBYuPIu0XjArK2OsXdsFvXvXkjc40nlMhN7FWWNERLnqzp0o9O+/D5cuhUtlbds6YOvWHihXzkLGyIjeYCL0Ls4aIyLKNaGh0XByWouEhFQAgKGhHubNa4fJk12gp6eQOTqiNzhY+l0aY4Q4a4yI6GNUqmSFnj1rAACqVSuJv/8ega++as4kiAoUtgi9i4uuEhHlqpUrO6FCBUtMm9YKpqaGcodDlM5HtQglJiZ+uFJhwlljREQ5kpiYiokTj2HPnpsa5ZaWxpg3rz2TICqwtE6E1Go1vvvuO5QtWxZmZmYIDQ0FAMyYMQMbN27M9QDzFWeNERFp7fr1SDRpsh7Llp3HZ58dwsOHMXKHRJRtWidCc+fOhY+PDxYuXAilUimV165dGxs2bMjV4PIdW4SIiLJNrRZYvvxvNG68HtevPwUAJCSk4OLFJzJHRpR9WidCW7duxbp169C/f3/o6+tL5fXq1cOdO3dyNbh8x+nzRETZEh7+Cp067cCECf5ISlIBAOrUscHFi5+hR48aMkdHlH1aD5Z+/PgxKleunK5crVYjJSUlV4KSTSrXGiMi+pCDB+9gxIjfEBX1WiqbOLEZ5s9vD2NjzsGhwkXr39iaNWvi9OnTqFChgkb53r170aBBg1wLTBacNUZElKn4+GRMnvw71q4Nksrs7Mzg4+OBjh0dZYyMKOe0ToRmzpyJwYMH4/Hjx1Cr1di3bx+Cg4OxdetWHDp0KC9izD8aLULKzOsREemg2Ngk/Prrbem5h0d1rF/fFdbWpjJGRfRxtB4j1L17d/z22284fvw4ihUrhpkzZ+L27dv47bff0KFDh7yIMf+kzRozMAYUvOEXEdG77OzMsWFDV5iaGmL9+q7Yt68PkyAq9BRCpC2BpxtiY2NhaWmJmJgYWFi8t87NpupAdDBgVBwYGy1LfEREBcXDhzEoVkyJEiVMNMqfPo2HjU0xmaIiXZXl9/dH0LpFqFKlSnj+/Hm68pcvX6JSpUq5EpRs0sYIccYYEem43btvom7dNRg16hDe/3uZSRAVJVonQmFhYVCpVOnKk5KS8Pjx41wJSjZpY4Q4UJqIdFRsbBKGDDkAT8+9ePkyEXv33oKv73W5wyLKM9keLO3n5yf97O/vD0tLS+m5SqXCiRMn4ODgkKvB5bu0FiFOnSciHRQY+BD9++/D/fsvpTJPz1ro1KmKfEER5bFsJ0IeHh4AAIVCgcGDB2tsMzQ0hIODA5YsWZKrweW7VHaNEZHuSU1VY968v/Ddd39BpXrTDWZursTKlZ0wYEBdKDh5hIqwbCdCarUaAFCxYkX8888/sLa2zrOgZCGE5qwxIiIdEBoajQED9iEw8JFU5uJij+3be6BiRSsZIyPKH1rfR+j+/ft5EYf8VMlvf+YYISLSAXfvvoCT01q8evXm809fX4GZM1vjm29awsBA6yGkRIVSju6FHh8fj1OnTuHBgwdITk7W2DZ+/PhcCSzfcZ0xItIxjo5WaN++Eg4cuINKlaywY0dPNGtWTu6wiPKV1onQ5cuX0alTJ7x+/Rrx8fEoUaIEoqKiYGpqChsbm8KbCKVyeQ0i0i0KhQLr13dFhQqW+O67tjA350QR0j1at31OnDgRXbt2RXR0NExMTPD333/jv//+Q8OGDbF48eK8iDF/qLjgKhEVXcnJKnh7H8fhwyEa5dbWpli2zJ1JEOksrROhK1euYPLkydDT04O+vj6SkpJgb2+PhQsX4ptvvsmLGPNHKrvGiKhoCg6OgrPzRvzww1kMG+aHyMg4uUMiKjC0ToQMDQ2hp/dmNxsbGzx48AAAYGlpiYcPH+ZudPmJiRARFTFCCKxdexENGqzFpUvhAIDo6AScPVuIP6uJcpnWY4QaNGiAf/75B1WqVEHr1q0xc+ZMREVFYdu2bahdu3ZexJg/0qbOAxwjRESF3rNn8Rgx4jf4+QVLZdWqlYSvby84OdnJGBlRwaJ1i9D8+fNhZ/fmP9G8efNgZWWFMWPG4NmzZ1i7dm2uB5hvOGuMiIoIf/+7qFt3jUYSNGZMI1y6NIpJENF7tG4RatSokfSzjY0Njh07lqsByYazxoiokEtMTMXUqcexbNl5qcza2hSbNnVD167VZIyMqODKtTtmXbp0CV26dMmtw+U/jTFCnD1BRIXP06fx2Lz5ivTc3b0yrl8fwySIKAtaJUL+/v6YMmUKvvnmG4SGhgIA7ty5Aw8PDzRu3FhahqNQUrFFiIgKt/LlLbF6dWcYGeljxQp3HDniBVtbM7nDIirQst01tnHjRowcORIlSpRAdHQ0NmzYgKVLl2LcuHHw9PTEjRs3UKNGjbyMNW9x1hgRFTLh4a9QrJgSFhZvW7H79auDFi3Kw97eUsbIiAqPbLcILV++HD/88AOioqKwe/duREVFYdWqVbh+/TrWrFlTuJMggC1CRFSoHDx4B3XrrsH48UfTbWMSRJR92U6E7t27h969ewMAevbsCQMDAyxatAjlyhWRdWlS35k+zxYhIiqg4uOTMXr0IXh47EJU1Gts2XIVv/56S+6wiAqtbHeNJSQkwNTUFMCb9WmMjIykafRFAqfPE1EBFxT0BF5e+xAS8lwq8/CojtatHeQLiqiQ02r6/IYNG2Bm9mbgXWpqKnx8fGBtba1Rh4uuEhHlLpVKjcWLz2H69JNITX0zKcXU1BDLl7tj+PAGUCgUMkdIVHhlOxEqX7481q9fLz23tbXFtm3bNOooFAqtE6GVK1di0aJFiIiIQL169fDTTz+hSZMmmdZ/+fIlpk2bhn379uHFixeoUKECli1bhk6dOml13nS46CoRFUAPH8Zg4MD9OHXqP6msYUM7+Pr2QtWqJWWMjKhoyHYiFBYWlusn37VrFyZNmoQ1a9agadOmWLZsGdzc3BAcHAwbG5t09ZOTk9GhQwfY2Nhg7969KFu2LP777z8UL17844PhrDEiKmBCQp6jadMNePnyzeeTQgF4e7fA7NltoFTqyxwdUdGg9Z2lc9PSpUsxcuRIDB06FACwZs0aHD58GJs2bYK3t3e6+ps2bcKLFy9w7tw5GBoaAgAcHBxyJxgmQkRUwFSuXAJNm5aFv/892NtbYNu2HhwPRJTLcu3O0tpKTk5GUFAQXF1d3wajpwdXV1cEBgZmuI+fnx+cnZ3xxRdfoHTp0qhduzbmz58PlUr18QFx0VUiKmD09BTYvLk7PvvMCVevjmYSRJQHZGsRioqKgkqlQunSpTXKS5cujTt37mS4T2hoKP7880/0798fR44cwd27d/H5558jJSUFs2bNynCfpKQkJCW9TXJiY2MzDoizxohIRqmpasyb9xdatqyAdu0qSuV2duZYu7arjJERFW2ydo1pS61Ww8bGBuvWrYO+vj4aNmyIx48fY9GiRZkmQgsWLMCcOXM+fHDOGiMimYSGRmPAgH0IDHyEsmXNce3aGJQoYSJ3WEQ6QbauMWtra+jr6yMyMlKjPDIyEra2thnuY2dnh6pVq0Jf/+0gwRo1aiAiIgLJyckZ7jN16lTExMRIj4cPH2YcEGeNEVE+E0Jg69arqF9/DQIDHwEAIiLicPLkfZkjI9IdOUqE7t27h+nTp6Nfv354+vQpAODo0aO4efNmto+hVCrRsGFDnDhxQipTq9U4ceIEnJ2dM9ynefPmuHv3rsbiriEhIbCzs4NSqcxwHyMjI1hYWGg8MsTB0kSUj6KjE9C3768YPPgAXr1684dcpUpWOHNmGHr1qilzdES6Q+tE6NSpU6hTpw7Onz+Pffv2IS4uDgBw9erVTLunMjNp0iSsX78eW7Zswe3btzFmzBjEx8dLs8gGDRqEqVOnSvXHjBmDFy9e4Msvv0RISAgOHz6M+fPn44svvtD2ZaTHRIiI8klAQBjq1l2D3bvf/vE4ZEh9XLkyCs2aFZFli4gKCa3HCHl7e2Pu3LmYNGkSzM3NpfJ27drh559/1upYnp6eePbsGWbOnImIiAjUr18fx44dkwZQP3jwAHp6b3M1e3t7+Pv7Y+LEiahbty7Kli2LL7/8El9//bW2LyO9tK4xhT6gV6iGThFRIZGcrMKsWSfxww9nIcSbsuLFjbFuXRf07l1L3uCIdJRCiLT/jtljZmaG69evo2LFijA3N8fVq1dRqVIlhIWFoXr16khMTPzwQWQUGxsLS0tLxMTEaHaTbakDRN0ADIsB4+PkC5CIiqzQ0GjUrbsa8fEpAIA2bRywdasHV4snyoZMv78/ktZdY8WLF0d4eHi68suXL6Ns2bK5EpQs0rrGOGOMiPJIpUpWWL7cHYaGeli40BUnTgxiEkQkM637gPr27Yuvv/4ae/bsgUKhgFqtxtmzZzFlyhQMGjQoL2LMH2mJkAFnjBFR7oiKeg1TU0OYmhpKZcOGNUDr1g6oXLmEjJERURqtW4Tmz5+P6tWrw97eHnFxcahZsyZatWoFFxcXTJ8+PS9izB8qtggRUe7x97+LOnVW46uvftcoVygUTIKIChCtxwilefDgAW7cuIG4uDg0aNAAVapUye3Y8kSmfYwrzIGUOKBkTWBI9m8DQET0rsTEVEydehzLlp2Xyg4d6ofOnavKGBVR4ZdXY4S07ho7c+YMWrRogfLly6N8+fK5Fojs2CJERB/p+vVI9O+/D9evP5XK3N0ro2HDMjJGRURZ0bprrF27dqhYsSK++eYb3Lp1Ky9iyn9qFaBOffMz7yFERFpSqwWWL/8bjRuvl5IgIyN9rFjhjiNHvGBrayZzhESUGa0ToSdPnmDy5Mk4deoUateujfr162PRokV49OhRXsSXP95deZ6JEBFpITz8FTp12oEJE/yRlKQCANSpY4OLFz/DuHFNoVAoZI6QiLKidSJkbW2NsWPH4uzZs7h37x569+6NLVu2wMHBAe3atcuLGPMeF1wlohwIDo5C3bpr4O9/TyqbOLEZLlwYidq1bWSMjIiy66MWXa1YsSK8vb3x/fffo06dOjh16lRuxZW/uOAqEeVA5colULNmKQCAnZ0Z/P0HYOlSNxgb8+70RIVFjhOhs2fP4vPPP4ednR28vLxQu3ZtHD58ODdjyz9cZ4yIckBfXw/btvXAwIF1ce3aGHTs6Ch3SESkJa3/bJk6dSp27tyJJ0+eoEOHDli+fDm6d+8OU1PTvIgvf6jYNUZEWVOp1Fi8+BxatqwAFxd7qbx8eUts3dpDxsiI6GNonQj99ddf+Oqrr9CnTx9YW1vnRUz5L5WDpYkocw8fxmDgwP04deo/VKxYHFeujIaFBbvRiYoCrROhs2fP5kUc8lKxa4yIMrZ7902MGnUIL1+++ZwIC3uJ33+/h08/rSlzZESUG7KVCPn5+eGTTz6BoaEh/Pz8sqzbrVu3XAksX3HWGBG9JzY2CePHH8WWLVelMnt7C2zb1gOtWzvIFxgR5apsJUIeHh6IiIiAjY0NPDw8Mq2nUCigUqlyK7b8w1ljRPSOwMCHGDBgP0JDo6UyT89aWL26M6ysTGSMjIhyW7YSIbVaneHPRQZnjRERgNRUNebN+wvfffcXVKo3yzCamyuxcmUnDBhQlzdHJCqCtJ4+v3XrViQlJaUrT05OxtatW3MlqHzHRIiIANy79wILFpyRkiAXF3tcvToaAwfWYxJEVERpnQgNHToUMTEx6cpfvXqFoUOH5kpQ+Y7T54kIQLVq1li4sAP09RWYM6cNTp0agooVreQOi4jykNazxoQQGf5l9OjRI1haWuZKUPmOa40R6aTo6ASYmhrCyOjtR+G4cU3Qrl1FLpFBpCOynQg1aNAACoUCCoUC7du3h4HB211VKhXu378Pd3f3PAkyz3HWGJHOCQgIw8CB+9G3by0sWtRRKlcoFEyCiHRIthOhtNliV65cgZubG8zMzKRtSqUSDg4O6NWrV64HmC9SOWuMSFckJ6swa9ZJ/PDDWQgBLF4cCHf3ymjfvpLcoRGRDLKdCM2aNQsA4ODgAE9PTxgbF6GWE95QkUgnBAdHwctrHy5dCpfK2rZ1QLVqReQu+USkNa3HCA0ePDgv4pAXZ40RFWlCCKxbF4SJE/2RkJAKADA01MO8ee0webIL9PQ4I4xIV2UrESpRogRCQkJgbW0NKyurLKeRvnjxIteCyzecNUZUZD17Fo8RI36Dn1+wVFatWkn4+vaCk5OdjJERUUGQrUToxx9/hLm5ufRzkbufBmeNERVJwcFRaNNmCyIi4qSyMWMaYfHijjA1NZQxMiIqKLKVCL3bHTZkyJC8ikU+nDVGVCRVqmQFe3sLRETEwdraFJs2dUPXrtXkDouIChCtb6h46dIlXL9+XXp+8OBBeHh44JtvvkFycnKuBpdvOEaIqEgyNNTHjh090bNnDVy/PoZJEBGlo3UiNGrUKISEhAAAQkND4enpCVNTU+zZswf/+9//cj3AfMFFV4kKPbVaYMWK87h8OVyjvEqVkvj11z6wtTXLZE8i0mVaJ0IhISGoX78+AGDPnj1o3bo1fH194ePjg19//TW348sfbBEiKtTCw1+hU6cd+PLLY/Dy2ofXr1PkDomICgmtEyEhhLQC/fHjx9GpUycAgL29PaKionI3uvzCWWNEhdbBg3dQt+4a+PvfAwDcuROFo0f/lTkqIiostL6PUKNGjTB37ly4urri1KlTWL16NQDg/v37KF26dK4HmC80WoTYNUZUGMTHJ2Py5N+xdm2QVGZnZwYfHw907OgoY2REVJhonQgtW7YM/fv3x4EDBzBt2jRUrlwZALB37164uLjkeoD5Im36vL4SUGjdSEZE+Swo6Am8vPYhJOS5VObhUR3r13eFtbWpjJERUWGjdSJUt25djVljaRYtWgR9ff1cCSrfpbUIsVuMqEBTqdRYtOgcZsw4idTUN130pqaGWLbMDSNGOBW9e5wRUZ7TOhFKExQUhNu3bwMAatasCScnp1wLKt+ljRHijDGiAu3OnSiNJKhhQzv4+vZC1aolZY6MiAorrROhp0+fwtPTE6dOnULx4sUBAC9fvkTbtm2xc+dOlCpVKrdjzHtpLUKcMUZUoNWqZYPvvmuLb745AW/vFpg9uw2UykLaEk1EBYLWA2LGjRuHuLg43Lx5Ey9evMCLFy9w48YNxMbGYvz48XkRY95TMREiKohevUqSWn/SfPWVCy5cGIn589szCSKij6Z1InTs2DGsWrUKNWrUkMpq1qyJlStX4ujRo7kaXL7hGCGiAicw8CHq11+LuXP/0ijX19dDo0ZlZIqKiIoarRMhtVoNQ8P0ixUaGhpK9xcqVIR4O2uMLUJEsktNVWPOnAC0bLkZoaHR+O67v3Du3EO5wyKiIkrrRKhdu3b48ssv8eTJE6ns8ePHmDhxItq3b5+rweULdSog/j+BY4sQkaxCQ6PRqtVmzJ59CiqVAAA0a1YOdnZcHoOI8obWidDPP/+M2NhYODg4wNHREY6OjqhYsSJiY2Px008/5UWMeYvrjBHJTgiBrVuvon79NQgMfAQA0NdXYM6cNjh1aggqVrSSN0AiKrK0njVmb2+PS5cu4cSJE9L0+Ro1asDV1TXXg8sXXGeMSFbR0QkYM+Ywdu26KZVVqmSFHTt6olmzcjJGRkS6QKtEaNeuXfDz80NycjLat2+PcePG5VVc+YeJEJFsgoOj0KHDNjx8GCuVDRlSHytWuMPcnC20RJT3sp0IrV69Gl988QWqVKkCExMT7Nu3D/fu3cOiRYvyMr68xwVXiWRToUJxFC9ujIcPY2FlZYy1a7ugd+9acodFRDok22OEfv75Z8yaNQvBwcG4cuUKtmzZglWrVuVlbPmDLUJEsjE2NoCvby906lQF166NYRJERPku24lQaGgoBg8eLD338vJCamoqwsPD8ySwfJM2dR5gixBRHhJCYN26INy69UyjvHZtGxw+7IVy5SxkioyIdFm2E6GkpCQUK1bs7Y56elAqlUhISMiTwPINW4SI8tyzZ/Hw8NiFUaMOwcvrVyQlpcodEhERAC0HS8+YMQOmpqbS8+TkZMybNw+WlpZS2dKlS3MvuvzA6fNEecrf/y6GDDmIiIg4AMDVq5E4dCgEvXrVlDkyIiItEqFWrVohODhYo8zFxQWhoaHSc4VCkXuR5Re2CBHlicTEVHh7H8fy5eelMmtrU2za1A1du1aTMTIioreynQgFBATkYRgy4qwxolx3/XokvLz24caNp1KZm5sjfHw8YGvLu0QTUcGh9Q0Vixy2CBHlGrVa4KefzuPrr48jKUkFADAy0sfChR0wdmwT6OkVwlZjIirSmAhx1hhRrrl+PRKTJv0OtfrNOmF16tjA17cXate2kTkyIqKMab3WWJHDFiGiXFOvni2++aYFAGDixGa4cGEkkyAiKtDYIsRZY0Q59vp1CoyNDTS6vGbObI2OHR3RsmUFGSMjIsoetgixRYgoR4KCnqBBg7VYsuScRrmhoT6TICIqNHKUCJ0+fRoDBgyAs7MzHj9+DADYtm0bzpw5k6vB5QvOGiPSikqlxg8/nEGzZhsREvIc06b9iUuXCvkd5olIZ2mdCP36669wc3ODiYkJLl++jKSkN4ONY2JiMH/+/FwPMM+xRYgo2x4+jEH79lvh7X0CqalqAEDduqVhZqaUOTIiopzROhGaO3cu1qxZg/Xr18PQ0FAqb968OS5dupSrweWLd2eNMREiytTu3TdRt+4anDr1HwBAoQCmTm2Bc+eGo2rVkjJHR0SUM1oPlg4ODkarVq3SlVtaWuLly5e5EVP+SmXXGFFWYmOTMH78UWzZclUqs7e3wLZtPdC6tYN8gRER5QKtEyFbW1vcvXsXDg4OGuVnzpxBpUqVciuu/MNZY0SZCg6OQqdOvggNjZbKPD1rYc2aLihenH84EFHhp3XX2MiRI/Hll1/i/PnzUCgUePLkCXbs2IEpU6ZgzJgxeRFj3uIYIaJMlStnAQODNx8T5uZKbN3qgV9+6cUkiIiKDK0TIW9vb3h5eaF9+/aIi4tDq1atMGLECIwaNQrjxo3LURArV66Eg4MDjI2N0bRpU1y4cCFb++3cuRMKhQIeHh45Oi8AJkJEWShWTAlf355o08YBV6+OxsCB9Qrn4spERJlQCCFETnZMTk7G3bt3ERcXh5o1a8LMLGcLKe7atQuDBg3CmjVr0LRpUyxbtgx79uxBcHAwbGwyvyNtWFgYWrRogUqVKqFEiRI4cOBAts4XGxsLS0tLxMTEwMLCAtjbEfjvjzcbx8YARhY5eh1EhZ0QAtu2XUPz5vZwdCyRbhsTICKSU7rv71yS4xsqKpVK1KxZE02aNMlxEgQAS5cuxciRIzF06FDUrFkTa9asgampKTZt2pTpPiqVCv3798ecOXM+flwSW4SIEB2dgL59f8XgwQfQv/8+pKSoNLYzCSKiokrrwdJt27bN8kPxzz//zPaxkpOTERQUhKlTp0plenp6cHV1RWBgYKb7ffvtt7CxscHw4cNx+vTpLM+RlJQk3esIeJNRapCmzysAPUMQ6ZqAgDAMHLgfjx69+b9x/vxjHDoUgh49asgcGRFR3tM6Eapfv77G85SUFFy5cgU3btzA4MGDtTpWVFQUVCoVSpcurVFeunRp3LlzJ8N9zpw5g40bN+LKlSvZOseCBQswZ86czCukzRozMH5zYxQiHZGcrMLMmSexcOFZpHWQW1kZY926rkyCiEhnaJ0I/fjjjxmWz549G3FxcR8dUFZevXqFgQMHYv369bC2ts7WPlOnTsWkSZOk57GxsbC3t39bIa1rjFPnSYcEB0fBy2ufxtIYbds6YOvWHihXjuPkiEh35Nrq8wMGDECTJk2wePHibO9jbW0NfX19REZGapRHRkbC1tY2Xf179+4hLCwMXbt2lcrU6je3+TcwMEBwcDAcHR019jEyMoKRURZJTuo7LUJERZwQAuvWBWHiRH8kJKQCAAwN9TBvXjtMnuyisYo8EZEuyLVEKDAwEMbG2iUTSqUSDRs2xIkTJ6Qp8Gq1GidOnMDYsWPT1a9evTquX7+uUTZ9+nS8evUKy5cv12zpya60rjHeVZp0wOXLERg9+rD0vFq1kvD17QUnJzsZoyIiko/WiVDPnj01ngshEB4ejosXL2LGjBlaBzBp0iQMHjwYjRo1QpMmTbBs2TLEx8dj6NChAIBBgwahbNmyWLBgAYyNjVG7dm2N/YsXLw4A6cqzjS1CpEOcnOwwaVIzLF36N8aMaYTFizvC1JSTBIhId2mdCFlaWmo819PTQ7Vq1fDtt9+iY8eOWgfg6emJZ8+eYebMmYiIiED9+vVx7NgxaQD1gwcPoKeX41n+H5Y2a4wtQlQEJSWlQqnU15jpOX9+e7i7V0aHDo5Z7ElEpBu0uqGiSqXC2bNnUadOHVhZWeVlXHlG44ZM5ubA0v9PsuyaAV6ZT9knKmyuX4+El9c+jBnTCJ9/3ljucIiIPkqBuKGivr4+OnbsWDhXmc+I6u39hThrjIoKtVpg+fK/0bjxety48RSTJ/+OW7eeyR0WEVGBpHXXWO3atREaGoqKFSvmRTz5i3eVpiImPPwVhg49CH//e1JZlSolstiDiEi3aT34Zu7cuZgyZQoOHTqE8PBwxMbGajwKFdU7iRDHCFEhd/DgHdStu0YjCZo4sRkuXBiJmjVLyRgZEVHBle0WoW+//RaTJ09Gp06dAADdunXTGICZtiijSqXK7BAFD1uEqAiIj0/G5Mm/Y+3aIKnMzs4MPj4e6NiRA6KJiLKS7URozpw5GD16NE6ePJmX8eQvJkJUyIWEPEfXrr8gJOS5VObhUR3r13eFtbWpjJERERUO2U6E0iaXtW7dOs+CyXcag6WZCFHhU7p0MSQnv2mFNTU1xPLl7hg+vAFXiyciyiatxggVuQ9XFVuEqHCztDTG9u090LRpWVy+PAojRjgVvf+nRER5SKtZY1WrVv3gh+yLFy8+KqB89W7XGKfPUyGwZ89NNGtWDvb2b29s2rx5eQQGDmcCRESUA1olQnPmzEl3Z+lCjbPGqJCIjU3C+PFHsWXLVbRp44DjxwdCX/9tgy6TICKinNEqEerbty9sbGzyKpb8x8HSVAgEBj7EgAH7ERoaDQAICAjDoUMh6N69usyREREVftkeI1Qk/+JkIkQFWGqqGnPmBKBly81SEmRursTWrR7o1q2azNERERUNWs8aK1I4a4wKqNDQaAwYsA+BgY+kMhcXe2zf3gMVKxbOdf6IiAqibCdCarU6L+OQB2eNUQEjhMC2bdcwduwRvHqVDADQ11dg5szW+OabljAw0Ppm8ERElAWt1xorUjhrjAqYixefYPDgA9LzSpWssGNHTzRrVk6+oIiIijDd/vOSY4SogGncuCxGjWoIABgypD6uXBnFJIiIKA/pdosQp8+TzFJSVDAw0NOYjLBkSUd06lSFA6KJiPIBW4TSsEWI8llwcBSaNduILVuuapQXK6ZkEkRElE90OxHirDGSgRACa9deRIMGa3HpUjjGjTuKu3cL0R3ZiYiKEN3uGmOLEOWzZ8/iMWLEb/DzC5bKypY1R0JCioxRERHpLt1OhFScNUb5x9//LoYMOYiIiDipbPTohliyxA2mpoYyRkZEpLt0OxFiixDlg8TEVEydehzLlp2XyqytTbFpUzd07cqxQEREctLtRIizxiiP3b37Aj177sL160+lMnf3yti8uTtsbc1kjIyIiABdT4TYIkR5zMrKGM+fJwAAjIz0sWhRB4wd26Rort1HRFQI6fisMSZClLdKljSFj0931KtXGhcvfoZx45oyCSIiKkB0vEXo3enzHCxNH++334LRuHFZjW6vDh0cERRUEfr6uv13BxFRQaTbn8xpLUJ6Bm8eRDkUH5+M0aMPoVu3nRg27CCEEBrbmQQRERVMuv3pnDZGiK1B9BGCgp7AyWkd1q4NAgAcPXoXhw6FyBwVERFlh24nQmktQpwxRjmgUqnxww9n0KzZRoSEPAcAmJoaYv36rujSparM0RERUXbodn9QWosQB0qTlh4+jMHAgftx6tR/UlnDhnbw9e2FqlVLyhgZERFpg4kQwESItLJr1w2MHn0YL1+++f1RKABv7xaYPbsNlEp9maMjIiJt6HYilLboKrvGKJv+/vsR+vb9VXpub2+Bbdt6oHVrB/mCIiKiHOMYIYAtQpRtzZqVw8CBdQEAnp61cPXqaCZBRESFmO62CKlT3zwAzhqjTKnVAnp6mjdA/PnnTujcuQr69KnFmyMSERVyutsipHrnZopsEaIMhIZGo0WLTdi9+6ZGuYWFETw9azMJIiIqAnS3RUjjrtJMhOgtIQS2bbuGsWOP4NWrZNy+fQjOzuVgb28pd2hERJTLdLdFiAuuUgaioxPQt++vGDz4AF69SgYAlChhIi2cSkRERYvutgi9u+AqW4QIQEBAGAYO3I9Hj2KlsiFD6mPFCneYm3McGRFRUaS7iZA6+e3PbBHSacnJKsyceRILF55F2hJhxYsbY926Lujdu5a8wRERUZ7S3UTo3a4xzhrTWaGh0ejdew8uXQqXytq0ccDWrR4cE0REpAN0eIwQZ40RYGJigAcPYgAAhoZ6WLjQFSdODGISRESkI3Q3EeIYIQJgZ2eOjRu7oXp1a/z99wh89VXzdPcNIiKiokuHu8bYIqSLjh8PRYMGtihZ0lQq69atGj75pDIMDblOGBGRrtHdFiE1W4R0SWJiKiZOPIYOHbZh1KhDEGmjov8fkyAiIt2ku4kQW4R0xvXrkWjSZD2WLTsPAPj119s4duyuzFEREVFBoLuJEJfYKPLUaoHly/9G48brcf36UwCAkZE+Vqxwh7t7ZZmjIyKigkCHxwhx+nxRFh7+CkOHHoS//z2prE4dG/j69kLt2jYyRkZERAWJ7iZCKq41VlT5+QVj+HA/REW9lsomTmyG+fPbw9hYd3/liYgoPd39VlBxrbGi6OzZB+jefaf03NbWDFu2eKBjR0cZoyIiooJKd8cIcbB0keTiYo8ePaoDALp3r4br18cwCSIiokyxRQhg11ghJoSAQvH2BogKhQLr13dFt27VMHhwPY1tRERE79PdFiHOGiv0Hj6MQbt2W3HoUIhGecmSphgypD6TICIi+iDdbRF6t2uMs8YKnd27b2LUqEN4+TIRN28+xbVrY2BrayZ3WEREVMjocIsQu8YKo9jYJAwZcgCennvx8uWba2hsbIAnT17JHBkRERVGutsixK6xQicw8CH699+H+/dfSmWenrWwenVnWFmZyBcYEREVWrqbCKVy+nxhkZqqxty5f2Hu3L+gUr1ZI8zcXImVKzthwIC6HAtEREQ5pruJEG+oWCiEhb2El9evCAx8JJW5uNhj+/YeqFjRSsbIiIioKNDhMULsGisM9PQUuHXrGQBAX1+BOXPa4NSpIUyCiIgoV+huIqSx1phSvjgoS+XLW2LNmi6oVMkKZ84Mw8yZrWFgoLu/tkRElLt09xslrUVIXwkodPdtKGhOn/4PsbFJGmV9+9bGzZufo1mzcjJFRURERVWByABWrlwJBwcHGBsbo2nTprhw4UKmddevX4+WLVvCysoKVlZWcHV1zbJ+ptKmz3N8UIGQnKyCt/dxtG7tg3HjjqbbzsVSiYgoL8ieCO3atQuTJk3CrFmzcOnSJdSrVw9ubm54+vRphvUDAgLQr18/nDx5EoGBgbC3t0fHjh3x+PFj7U6cdkNFjg+SXXBwFJydN+KHH85CCGDr1qv4/fd7codFREQ6QCGEEHIG0LRpUzRu3Bg///wzAECtVsPe3h7jxo2Dt7f3B/dXqVSwsrLCzz//jEGDBn2wfmxsLCwtLRGz1AYW6qeAeXngs/8++nWQ9oQQWLcuCBMn+iMhIRUAYGioh3nz2mHyZBfo6XFaPBERvSF9f8fEwMLCIteOK2t/Q3JyMoKCgjB16lSpTE9PD66urggMDMzWMV6/fo2UlBSUKFEiw+1JSUlISno75iQ2NvbND6pkQAG2CMnk2bN4jBjxG/z8gqWyatVKwte3F5yc7GSMjIiIdImsXWNRUVFQqVQoXbq0Rnnp0qURERGRrWN8/fXXKFOmDFxdXTPcvmDBAlhaWkoPe3v7NxvSxggxEcp3/v53UbfuGo0kaMyYRrh0aRSTICIiyleyjxH6GN9//z127tyJ/fv3w9g444Rm6tSpiImJkR4PHz58syFt+jwXXM1Xp0//B3f3HYiIiAMAWFubws+vL1at6gxTU0OZoyMiIl0ja9eYtbU19PX1ERkZqVEeGRkJW1vbLPddvHgxvv/+exw/fhx169bNtJ6RkRGMjLJIdjhrLF+1aFEe7u6VcezYXbi7V8bmzd25ajwREclG1hYhpVKJhg0b4sSJE1KZWq3GiRMn4OzsnOl+CxcuxHfffYdjx46hUaNGHxcEu8bylUKhwObN3bFqVSccOeLFJIiIiGQle9fYpEmTsH79emzZsgW3b9/GmDFjEB8fj6FDhwIABg0apDGY+ocffsCMGTOwadMmODg4ICIiAhEREYiLi8tZAGwRyjMREXHo3NkXJ06EapTb2pphzJjGXCyViIhkJ/td6jw9PfHs2TPMnDkTERERqF+/Po4dOyYNoH7w4AH09N7ma6tXr0ZycjI+/fRTjePMmjULs2fP1j4AtgjlCT+/YAwf7oeoqNe4ejUCV6+ORsmSpnKHRUREpEH2RAgAxo4di7Fjx2a4LSAgQON5WFhY7p6ciVCuio9PxuTJv2Pt2iCpTK0WCAt7yUSIiIgKnAKRCMmKs8ZyTVDQE/Tvvw/Bwc+lMg+P6li/viusrZkEERFRwcNEiGOEPppKpcbixecwffpJpKaqAQCmpoZYvtwdw4c34FggIiIqsJgIsWvsozx6FIuBA/cjICBMKmvY0A6+vr1QtWpJ+QIjIiLKBtlnjcmOidBHSUhIwT//vFnwVqEApk5tgXPnhjMJIiKiQoGJELvGPkqVKiWxYsUnsLe3wMmTgzF/fnsolfpyh0VERJQtTITYIqSVCxce4/XrFI2yoUPr49atL9C6tYM8QREREeUQEyHOGsuW1FQ15swJgIvLRkyZ8rvGNoVCATMzpUyRERER5RwTIXaNfVBoaDRatdqM2bNPQaUSWL36Ik6evC93WERERB+Ns8bYNZYpIQS2bbuGsWOP4NWrZACAvr4CM2e2RsuWFWSOjoiI6OMxEWIilKHo6ASMGXMYu3bdlMoqVbLCjh090axZORkjIyIiyj1MhNg1ls6pU2EYOHA/Hj6MlcqGDKmPFSvcYW7OMVVERFR0MBFii5CGU6fC0LbtFgjx5rmVlTHWru2C3r1ryRsYERFRHuBgabYIaWjRojxatXoz/qdtWwdcuzaGSRARERVZbBEyYFfPu/T19bBtWw/s2XMLEyY0g54e1wkjIqKiiy1COtwi9OxZPHr12o2zZx9olNvbW2LSJGcmQUREVOSxRUhHxwj5+9/FkCEHERERh0uXwnH16mhYWLB1jIiIdAtbhHSsRSgxMRUTJhyDu/sORETEAQDi4pIREvJc5siIiIjyH1uEdKhF6Pr1SHh57cONG0+lMnf3yti8uTtsbc1kjIyIiEgeTIR0IBFSqwV++uk8vv76OJKSVAAAIyN9LFrUAWPHNoFCwbFARESkm5gIFfFFV8PDX2Ho0IPw978nldWpYwNf316oXdtGxsiIiIjkp+NjhBSAnqHcQeSpFy8SEBAQJj2fOLEZLlwYySSIiIgIup4IGRgDRbxbqFYtGyxa1AG2tmbw9x+ApUvdYGzMhkAiIiKAiZDcEeS6q1cjkJSUqlE2dmwT3Lr1OTp2dJQpKiIiooJJtxOhIjR1XqVS44cfzqBRo/WYNu1PjW0KhQJWViYyRUZERFRw6XYiVERahB4+jEH79lvh7X0CqalqLFkSiDNnHnx4RyIiIh2n24NFisCMsd27b2LUqEN4+TIRwJshT97eLdCkSVmZIyMiIir4dDwRKrwtQrGxSRg//ii2bLkqldnbW2Dbth5o3dpBvsCIiIgKEd1OhApp11hg4EMMGLAfoaHRUpmnZy2sXt2ZY4GIiIi0wESokAkICIOr61aoVAIAYG6uxMqVnTBgQF3eIZqIiEhLuj1YuhB2jTVvbo+GDcsAAFxc7HH16mgMHFiPSRAREVEOsEWokDE01MeOHT2xa9cNfP11CxgY6HYuS0RE9DF0OxEq4C1C0dEJGDv2KCZNaia1AgFA5colMG1aKxkjIypchBBITU2FSqWSOxQiyoKhoSH09fXz9Zy6nQgZFNzp8wEBYRg4cD8ePYpFUNATXLo0CqamRXtdNKK8kJycjPDwcLx+/VruUIjoAxQKBcqVKwczM7N8O6duJ0IFsEUoOVmFmTNPYuHCsxBvxkPj6dN43Lz5FI0b895ARNpQq9W4f/8+9PX1UaZMGSiVSo6nIyqghBB49uwZHj16hCpVquRby5BuJ0IFbIxQcHAUvLz24dKlcKmsbVsHbN3aA+XKWcgYGVHhlJycDLVaDXt7e5iamsodDhF9QKlSpRAWFoaUlBQmQvmigLQICSGwbl0QJk70R0LCmwVTDQ31MG9eO0ye7AI9Pf4FS/Qx9PQ4qYCoMJCjxVa3E6EC0CL07Fk8Roz4DX5+wVJZtWol4evbC05OdjJGRkREVPTpdiJUAFqEHj6MxZEj/0rPx4xphMWLO3JgNBERUT7Q7fbiAjBrzMnJDnPntoW1tSn8/Ppi1arOTIKIqEDZuHEjOnbsKHcYObZmzRp07do1W3WfP38OGxsbhIWF5W1QOqhv375YsmSJ3GGko9uJkAwtQnfuRCElRfNeJlOmuODmzc/RtWu1fI+HiAqeZ8+eYcyYMShfvjyMjIxga2sLNzc3nD17FsnJybC2tsb333+f4b7fffcdSpcujZSUFPj4+EChUKBGjRrp6u3ZswcKhQIODg5ZxpKYmIgZM2Zg1qxZAAAHBwcoFIpMH0OGDAGADLe1aNEi0/OEhYVBoVDgypUrGs/THubm5qhVqxa++OIL/Pvvvxr7pr3O9x8bNmwAAAwbNgyXLl3C6dOns3ytADBv3jx07979g+9LYbZnzx5Ur14dxsbGqFOnDo4cOfLBfVauXIkaNWrAxMQE1apVw9atWzW2p6Sk4Ntvv4WjoyOMjY1Rr149HDt2TKPO9OnTMW/ePMTExOTq6/lYup0I5eMYIbVaYPnyv1G//hrMnfuXxjZ9fT3Y2BTLt1iIqGDr1asXLl++jC1btiAkJAR+fn5o06YNnj9/DqVSiQEDBmDz5s3p9hNCwMfHB4MGDYKh4ZuW5WLFiuHp06cIDAzUqLtx40aUL1/+g7Hs3bsXFhYWaN68OQDgn3/+QXh4OMLDw/Hrr78CAIKDg6Wy5cuXS/tu3rxZKg8PD4efn5/W78Xx48cRHh6Oq1evYv78+bh9+zbq1auHEydOaNSzsLDQOFd4eDj69+8PAFAqlfDy8sKKFSuyPNfr16+xceNGDB8+XOs435WcnPxR++elc+fOoV+/fhg+fDguX74MDw8PeHh44MaNG5nus3r1akydOhWzZ8/GzZs3MWfOHHzxxRf47bffpDrTp0/H2rVr8dNPP+HWrVsYPXo0evTogcuXL0t1ateuDUdHR2zfvj1PX6PWhI6JiYkRAETMXAhxyzdfzvnkSaxwc9smgNkCmC309OaI8+cf5cu5iXRZQkKCuHXrlkhISJA7lGyLjo4WAERAQECmda5duyYAiNOnT2uUnzx5UgAQt2/fFkIIsXnzZmFpaSnGjh0rRowYIdV7+PChMDIyEt7e3qJChQpZxtO5c2cxZcqUDLelnS86OjrdNgBi//79WR77Xffv3xcAxOXLlzN8nkalUok2bdqIChUqiNTUVCHE29eZlVOnTgmlUilev36daZ09e/aIUqVKaZSlpqaKYcOGCQcHB2FsbCyqVq0qli1bplFn8ODBonv37mLu3LnCzs5OODg4CCGEePDggejdu7ewtLQUVlZWolu3buL+/fvSfhcuXBCurq6iZMmSwsLCQrRq1UoEBQVl+To+Vp8+fUTnzp01ypo2bSpGjRqV6T7Ozs7pfgcmTZokmjdvLj23s7MTP//8s0adnj17iv79+2uUzZkzR7Ro0SLTc2X1f1b6/o6JyXT/nNDtwdL50CJ08OAdjBjxG6Ki3t7Vdvz4Jqhbt3Sen5uIMrG9ERAfkb/nLGYLDLj4wWpmZmYwMzPDgQMH0KxZMxgZpR/LWKdOHTRu3BibNm3S6G7avHkzXFxcUL16dY36w4YNQ5s2bbB8+XKYmprCx8cH7u7uKF36w59DZ86cwcCBA7PxAvOHnp4evvzyS/To0QNBQUFo0qRJtvZr1KgRUlNTcf78ebRp0ybDOqdPn0bDhg01ytRqNcqVK4c9e/agZMmSOHfuHD777DPY2dmhT58+Ur0TJ07AwsICf/zxB4A3XUVubm5wdnbG6dOnYWBggLlz58Ld3R3Xrl2DUqnEq1evMHjwYPz0008QQmDJkiXo1KkT/v33X5ibm2cY444dOzBq1KgsX+vRo0fRsmXLDLcFBgZi0qRJGmVubm44cOBApsdLSkqCsbHm96WJiQkuXLiAlJQUGBoaZlrnzJkzGmVNmjTBvHnzkJSUlOHvthyYCOWR+PhkTJ78O9auDZLKbG3NsGWLBzp2dMyz8xJRNsRHAHGP5Y4iQwYGBvDx8cHIkSOxZs0aODk5oXXr1ujbty/q1q0r1Rs+fDimTJmCFStWwMzMDK9evcLevXsz7P5p0KABKlWqhL1792LgwIHw8fHB0qVLERoammUsL1++RExMDMqUKZNlvcz069dP46Z427dvh4eHR46O9a60RC8sLExKhGJiYjSWZTAzM0NExNtk19TUFJaWlvjvv/8yPe5///2X7rUaGhpizpw50vOKFSsiMDAQu3fv1kiEihUrhg0bNkCpVAJ481rVajU2bNgg3Rtn8+bNKF68OAICAtCxY0e0a9dO41zr1q1D8eLFcerUKXTp0iXDGLt164amTZtm/uYAKFs281UIIiIi0iXApUuX1niv3ufm5oYNGzbAw8MDTk5OCAoKwoYNG5CSkoKoqCjY2dnBzc0NS5cuRatWreDo6IgTJ05g37596db3K1OmDJKTkxEREYEKFSpk+Tryi24nQvp5k40GBT2Bl9c+hIQ8l8q6d6+GDRu6wdqad7clkl0x2wJ9zl69eqFz5844ffo0/v77bxw9ehQLFy7Ehg0bpMHI/fr1w8SJE7F7924MGzYMu3btgp6eHjw9PTM85rBhw7B582aUL18e8fHx6NSpE37++ecs40hISACAdH/pZ9ePP/4IV1dX6bmd3Zt7o33yySfSwOUKFSrg5s2bWh1X/P/6Q+/efM/c3ByXLl2Snmd0E00TE5Ms15xLSEjI8LWuXLkSmzZtwoMHD5CQkIDk5GTUr19fo06dOnWkJAgArl69irt376Zr2UlMTMS9e/cAAJGRkZg+fToCAgLw9OlTqFQqvH79Gg8ePMg0RnNz80xbi/LKjBkzEBERgWbNmkEIgdKlS2Pw4MFYuHCh9D4vX74cI0eORPXq1aFQKODo6IihQ4di06ZNGscyMTEBgAK19p+OJ0K53yL055/34ea2HampagCAqakhli1zw4gRTlzjiKigyEYXldyMjY3RoUMHdOjQATNmzMCIESMwa9YsKRGysLDAp59+is2bN0tJTp8+fTJdrLJ///743//+h9mzZ2PgwIEwMPjwx3/JkiWhUCgQHR2do9dga2uLypUrpyvfsGGDlGSlDerWxu3btwG8aZ1Jo6enl+G53vXixQuUKlUq0+3W1tbpXuvOnTsxZcoULFmyBM7OzjA3N8eiRYtw/vx5jXrFimlOeImLi0PDhg2xY8eOdOdJi2Hw4MF4/vw5li9fjgoVKsDIyAjOzs5ZDrb+2K4xW1tbREZGapRFRkbC1jbzRN3ExASbNm3C2rVrERkZCTs7O6xbtw7m5ubSaylVqhQOHDiAxMREPH/+HGXKlIG3tzcqVaqkcawXL15ovAcFgW4nQnnQNda8uT1q1iyFa9ci0bChHXx9e6Fq1ZK5fh4i0i01a9ZMN45j+PDhaNOmDQ4dOoRz585h0aJFme5fokQJdOvWDbt378aaNWuydU6lUomaNWvi1q1buXofoay6bj5ErVZjxYoVqFixIho0aJDt/e7du4fExMQs92nQoEG6GU1nz56Fi4sLPv/8c41jfYiTkxN27doFGxsbWFhkvFbk2bNnsWrVKnTq1AkA8PDhQ0RFRWV53I/tGnN2dsaJEycwYcIEqeyPP/6As7NzlscE3iSt5cqVA/AmQezSpUu6ljdjY2OULVsWKSkp+PXXXzW6DwHgxo0bKFeuHKytrT94vvzC6fO5zMjIAL6+PTFtWkucOzecSRARaeX58+do164dtm/fjmvXruH+/fvYs2cPFi5ciO7du2vUbdWqFSpXroxBgwahevXqcHFxyfLYPj4+iIqKSjeYOitubm7pBrzmp+fPnyMiIgKhoaHw8/ODq6srLly4gI0bN2q1KOfp06dRqVIlODpmPkbTzc0NN2/e1GgVqlKlCi5evAh/f3+EhIRgxowZ+Oeffz54vv79+8Pa2hrdu3fH6dOncf/+fQQEBGD8+PF49OiRdOxt27bh9u3bOH/+PPr37y91HWXG3NwclStXzvKR1TG+/PJLHDt2DEuWLMGdO3cwe/ZsXLx4EWPHjpXqTJ06FYMGDZKeh4SEYPv27fj3339x4cIF9O3bFzdu3MD8+fOlOufPn8e+ffsQGhqK06dPw93dHWq1Gv/73/80zn/69OkCd3NO3U6EPrJrLDY2CSNH+uHmzaca5bVq2WDu3HZQKvNn5VwiKjrMzMzQtGlT/Pjjj2jVqhVq166NGTNmYOTIkenG9CgUCgwbNgzR0dEYNmzYB49tYmKCkiW1++Ns+PDhOHLkiGw3wXN1dYWdnR3q1KkDb29v1KhRA9euXUPbtm21Os4vv/yCkSNHZlmnTp06cHJywu7du6WyUaNGoWfPnvD09ETTpk3x/PlzjdahzJiamuKvv/5C+fLl0bNnT9SoUQPDhw9HYmKi1EK0ceNGREdHw8nJCQMHDsT48eNhY2Oj1evSlouLC3x9fbFu3TrUq1cPe/fuxYEDB1C7dm2pTnh4uMY4JZVKhSVLlqBevXro0KEDEhMTce7cOY2bTiYmJmL69OmoWbMmevTogbJly+LMmTMoXry4Rp0DBw588DrkN4VIG3WmI2JjY2FpaYmYuYDFl48Bs5zNhggMfIgBA/YjNDQadeuWxoULI2BkpNs9jUQFTWJiIu7fv4+KFSvmeMAvAb1794aTkxOmTp0qdyg5cvPmTbRr1w4hISGwtLTMsu7hw4fx1Vdf4caNGxkOuKacW716Nfbv34/ff/890zpZ/Z+Vvr9jYjLtbswJ3b7KOWgRSk1VY86cALRsuRmhoW+aT+/fj8a1a5Ef2JOIqHBatGhRpoOwC4Pw8HBs3br1g0kQAHTu3BmfffYZHj8umLdXKMwMDQ3x008/yR1GOrrdIvS/OMAw+0tbhIZGY8CAfQgMfCSVubjYY/v2HqhY0SovwiWij8AWIaLCRY4WId3uy8nmfYSEENi27RrGjj2CV6/eTGvU11dg5szW+OabljAw0O2GNSIiosJKdxMhPX1A78MvPzo6AWPGHMauXW9v+FWpkhV27OiJZs3K5WWERERElMd0NxHK5vig27ejsGfPLen5kCH1sWKFO8zNC8YaKUT0YTo2AoCo0JLj/6ru9ulks1vMxcUe06a1RPHixti9+1Ns3tydSRBRIZF21+KCdDt/Ispc2l21tblH1Mdii9B77t+PRvnyltDXf5sjzpjRCqNGNUTZsrk3OIuI8p6+vj6KFy+Op0/f3OvL1NSUS90QFVBqtRrPnj2DqalptpaAyS26mwgZaLbqCCGwbl0QJk70x6xZrfH11y2kbYaG+kyCiAqptDWU0pIhIiq49PT0UL58+Xz9g0V3E6F3usaePYvHiBG/wc8vGAAwffpJdOzoiAYN7OSKjohyiUKhgJ2dHWxsbJCSkiJ3OESUBaVSme83siwQidDKlSuxaNEiREREoF69evjpp5/QpEmTTOvv2bMHM2bMQFhYGKpUqYIffvhBWrQu2/5/nTF//7sYMuQgIiLipE0jRjRAtWoFZ0E4Ivp4+vr6+TrugIgKB9kHS+/atQuTJk3CrFmzcOnSJdSrVw9ubm6ZNmOfO3cO/fr1w/Dhw3H58mV4eHjAw8MDN27c0Oq8iSoTTJhwDO7uO6QkyNraFH5+fbF6dReYmhp+9GsjIiKigk32O0s3bdoUjRs3lhYTVKvVsLe3x7hx4+Dt7Z2uvqenJ+Lj43Ho0CGprFmzZqhfvz7WrFnzwfOl3ZmyRtnxuP24hFTu7l4Zmzd3h61t4b2NPBERUVFVJNcaS05ORlBQEFxdXaUyPT09uLq6IjAwMMN9AgMDNeoDgJubW6b1M3P7sSkAwMhIHytWuOPIES8mQURERDpG1jFCUVFRUKlUKF26tEZ56dKlcefOnQz3iYiIyLB+REREhvWTkpKQlJQkPY+JiUnbgpo1S2Hjxu6oWbMUXr16lfMXQkRERHkqNjYWQO7fdLFADJbOSwsWLMCcOXMy2PIjbt0CnJ0n53tMRERElDPPnz+HpaVlrh1P1kTI2toa+vr6iIyM1CiPjIyU7v3xPltbW63qT506FZMmTZKev3z5EhUqVMCDBw9y9Y0k7cXGxsLe3h4PHz7M1f5eyhlej4KD16Lg4LUoOGJiYlC+fHmUKFHiw5W1IGsipFQq0bBhQ5w4cQIeHh4A3gyWPnHiBMaOHZvhPs7Ozjhx4gQmTJgglf3xxx9wdnbOsL6RkRGMjNIviWFpaclf6gLCwsKC16IA4fUoOHgtCg5ei4Ijt+8zJHvX2KRJkzB48GA0atQITZo0wbJlyxAfH4+hQ4cCAAYNGoSyZctiwYIFAIAvv/wSrVu3xpIlS9C5c2fs3LkTFy9exLp16+R8GURERFQIyZ4IeXp64tmzZ5g5cyYiIiJQv359HDt2TBoQ/eDBA43sz8XFBb6+vpg+fTq++eYbVKlSBQcOHEDt2rXleglERERUSMmeCAHA2LFjM+0KCwgISFfWu3dv9O7dO0fnMjIywqxZszLsLqP8xWtRsPB6FBy8FgUHr0XBkVfXQvYbKhIRERHJRfYlNoiIiIjkwkSIiIiIdBYTISIiItJZTISIiIhIZxXJRGjlypVwcHCAsbExmjZtigsXLmRZf8+ePahevTqMjY1Rp04dHDlyJJ8iLfq0uRbr169Hy5YtYWVlBSsrK7i6un7w2pF2tP2/kWbnzp1QKBTSjU/p42l7LV6+fIkvvvgCdnZ2MDIyQtWqVflZlUu0vRbLli1DtWrVYGJiAnt7e0ycOBGJiYn5FG3R9ddff6Fr164oU6YMFAoFDhw48MF9AgIC4OTkBCMjI1SuXBk+Pj7an1gUMTt37hRKpVJs2rRJ3Lx5U4wcOVIUL15cREZGZlj/7NmzQl9fXyxcuFDcunVLTJ8+XRgaGorr16/nc+RFj7bXwsvLS6xcuVJcvnxZ3L59WwwZMkRYWlqKR48e5XPkRZO21yPN/fv3RdmyZUXLli1F9+7d8yfYIk7ba5GUlCQaNWokOnXqJM6cOSPu378vAgICxJUrV/I58qJH22uxY8cOYWRkJHbs2CHu378v/P39hZ2dnZg4cWI+R170HDlyREybNk3s27dPABD79+/Psn5oaKgwNTUVkyZNErdu3RI//fST0NfXF8eOHdPqvEUuEWrSpIn44osvpOcqlUqUKVNGLFiwIMP6ffr0EZ07d9Yoa9q0qRg1alSexqkLtL0W70tNTRXm5uZiy5YteRWiTsnJ9UhNTRUuLi5iw4YNYvDgwUyEcom212L16tWiUqVKIjk5Ob9C1BnaXosvvvhCtGvXTqNs0qRJonnz5nkap67JTiL0v//9T9SqVUujzNPTU7i5uWl1riLVNZacnIygoCC4urpKZXp6enB1dUVgYGCG+wQGBmrUBwA3N7dM61P25ORavO/169dISUnJ9QX2dFFOr8e3334LGxsbDB8+PD/C1Ak5uRZ+fn5wdnbGF198gdKlS6N27dqYP38+VCpVfoVdJOXkWri4uCAoKEjqPgsNDcWRI0fQqVOnfImZ3sqt7+8CcWfp3BIVFQWVSiUtz5GmdOnSuHPnTob7REREZFg/IiIiz+LUBTm5Fu/7+uuvUaZMmXS/6KS9nFyPM2fOYOPGjbhy5Uo+RKg7cnItQkND8eeff6J///44cuQI7t69i88//xwpKSmYNWtWfoRdJOXkWnh5eSEqKgotWrSAEAKpqakYPXo0vvnmm/wImd6R2fd3bGwsEhISYGJikq3jFKkWISo6vv/+e+zcuRP79++HsbGx3OHonFevXmHgwIFYv349rK2t5Q5H56nVatjY2GDdunVo2LAhPD09MW3aNKxZs0bu0HROQEAA5s+fj1WrVuHSpUvYt28fDh8+jO+++07u0CiHilSLkLW1NfT19REZGalRHhkZCVtb2wz3sbW11ao+ZU9OrkWaxYsX4/vvv8fx48dRt27dvAxTZ2h7Pe7du4ewsDB07dpVKlOr1QAAAwMDBAcHw9HRMW+DLqJy8n/Dzs4OhoaG0NfXl8pq1KiBiIgIJCcnQ6lU5mnMRVVOrsWMGTMwcOBAjBgxAgBQp04dxMfH47PPPsO0adM0FgmnvJXZ97eFhUW2W4OAItYipFQq0bBhQ5w4cUIqU6vVOHHiBJydnTPcx9nZWaM+APzxxx+Z1qfsycm1AICFCxfiu+++w7Fjx9CoUaP8CFUnaHs9qlevjuvXr+PKlSvSo1u3bmjbti2uXLkCe3v7/Ay/SMnJ/43mzZvj7t27UjIKACEhIbCzs2MS9BFyci1ev36dLtlJS1AFl+7MV7n2/a3dOO6Cb+fOncLIyEj4+PiIW7duic8++0wUL15cRERECCGEGDhwoPD29pbqnz17VhgYGIjFixeL27dvi1mzZnH6fC7R9lp8//33QqlUir1794rw8HDp8erVK7leQpGi7fV4H2eN5R5tr8WDBw+Eubm5GDt2rAgODhaHDh0SNjY2Yu7cuXK9hCJD22sxa9YsYW5uLn755RcRGhoqfv/9d+Ho6Cj69Okj10soMl69eiUuX74sLl++LACIpUuXisuXL4v//vtPCCGEt7e3GDhwoFQ/bfr8V199JW7fvi1WrlzJ6fNpfvrpJ1G+fHmhVCpFkyZNxN9//y1ta926tRg8eLBG/d27d4uqVasKpVIpatWqJQ4fPpzPERdd2lyLChUqCADpHrNmzcr/wIsobf9vvIuJUO7S9lqcO3dONG3aVBgZGYlKlSqJefPmidTU1HyOumjS5lqkpKSI2bNnC0dHR2FsbCzs7e3F559/LqKjo/M/8CLm5MmTGX4HpL3/gwcPFq1bt063T/369YVSqRSVKlUSmzdv1vq8CiHYlkdERES6qUiNESIiIiLSBhMhIiIi0llMhIiIiEhnMREiIiIincVEiIiIiHQWEyEiIiLSWUyEiIiISGcxESIiDT4+PihevLjcYeSYQqHAgQMHsqwzZMgQeHh45Es8RFSwMREiKoKGDBkChUKR7nH37l25Q4OPj48Uj56eHsqVK4ehQ4fi6dOnuXL88PBwfPLJJwCAsLAwKBQKXLlyRaPO8uXL4ePjkyvny8zs2bOl16mvrw97e3t89tlnePHihVbHYdJGlLeK1OrzRPSWu7s7Nm/erFFWqlQpmaLRZGFhgeDgYKjValy9ehVDhw7FkydP4O/v/9HHzmzV8HdZWlp+9Hmyo1atWjh+/DhUKhVu376NYcOGISYmBrt27cqX8xPRh7FFiKiIMjIygq2trcZDX18fS5cuRZ06dVCsWDHY29vj888/R1xcXKbHuXr1Ktq2bQtzc3NYWFigYcOGuHjxorT9zJkzaNmyJUxMTGBvb4/x48cjPj4+y9gUCgVsbW1RpkwZfPLJJxg/fjyOHz+OhIQEqNVqfPvttyhXrhyMjIxQv359HDt2TNo3OTkZY8eOhZ2dHYyNjVGhQgUsWLBA49hpXWMVK1YEADRo0AAKhQJt2rQBoNnKsm7dOpQpU0ZjZXcA6N69O4YNGyY9P3jwIJycnGBsbIxKlSphzpw5SE1NzfJ1GhgYwNbWFmXLloWrqyt69+6NP/74Q9quUqkwfPhwVKxYESYmJqhWrRqWL18ubZ89eza2bNmCgwcPSq1LAQEBAICHDx+iT58+KF68OEqUKIHu3bsjLCwsy3iIKD0mQkQ6Rk9PDytWrMDNmzexZcsW/Pnnn/jf//6Xaf3+/fujXLly+OeffxAUFARvb28YGhoCAO7duwd3d3f06tUL165dw65du3DmzBmMHTtWq5hMTEygVquRmpqK5cuXY8mSJVi8eDGuXbsGNzc3dOvWDf/++y8AYMWKFfDz88Pu3bsRHByMHTt2wMHBIcPjXrhwAQBw/PhxhIeHY9++fenq9O7dG8+fP8fJkyelshcvXuDYsWPo378/AOD06dMYNGgQvvzyS9y6dQtr166Fj48P5s2bl+3XGBYWBn9/fyiVSqlMrVajXLly2LNnD27duoWZM2fim2++we7duwEAU6ZMQZ8+feDu7o7w8HCEh4fDxcUFKSkpcHNzg7m5OU6fPo2zZ8/CzMwM7u7uSE5OznZMRAQUydXniXTd4MGDhb6+vihWrJj0+PTTTzOsu2fPHlGyZEnp+ebNm4WlpaX03NzcXPj4+GS47/Dhw8Vnn32mUXb69Gmhp6cnEhISMtzn/eOHhISIqlWrikaNGgkhhChTpoyYN2+exj6NGzcWn3/+uRBCiHHjxol27doJtVqd4fEBiP379wshhLh//74AIC5fvqxRZ/DgwaJ79+7S8+7du4thw4ZJz9euXSvKlCkjVCqVEEKI9u3bi/nz52scY9u2bcLOzi7DGIQQYtasWUJPT08UK1ZMGBsbSytpL126NNN9hBDiiy++EL169co01rRzV6tWTeM9SEpKEiYmJsLf3z/L4xORJo4RIiqi2rZti9WrV0vPixUrBuBN68iCBQtw584dxMbGIjU1FYmJiXj9+jVMTU3THWfSpEkYMWIEtm3bJnXvODo6AnjTbXbt2jXs2LFDqi+EgFqtxv3791GjRo0MY4uJiYGZmRnUajUSExPRokULbNiwAbGxsXjy5AmaN2+uUb958+a4evUqgDfdWh06dEC1atXg7u6OLl26oGPHjh/1XvXv3x8jR47EqlWrYGRkhB07dqBv377Q09OTXufZs2c1WoBUKlWW7xsAVKtWDX5+fkhMTMT27dtx5coVjBs3TqPOypUrsWnTJjx48AAJCQlITk5G/fr1s4z36tWruHv3LszNzTXKExMTce/evRy8A0S6i4kQURFVrFgxVK5cWaMsLCwMXbp0wZgxYzBv3jyUKFECZ86cwfDhw5GcnJzhF/rs2bPh5eWFw4cP4+jRo5g1axZ27tyJHj16IC4uDqNGjcL48ePT7Ve+fPlMYzM3N8elS5egp6cHOzs7mJiYAABiY2M/+LqcnJxw//59HD16FMePH0efPn3g6uqKvXv3fnDfzHTt2hVCCBw+fBiNGzfG6dOn8eOPP0rb4+LiMGfOHPTs2TPdvsbGxpkeV6lUStfg+++/R+fOnTFnzhx89913AICdO3diypQpWLJkCZydnWFubo5Fixbh/PnzWcYbFxeHhg0baiSgaQrKgHiiwoKJEJEOCQoKglqtxpIlS6TWjrTxKFmpWrUqqlatiokTJ6Jfv37YvHkzevToAScnJ9y6dStdwvUhenp6Ge5jYWGBMmXK4OzZs2jdurVUfvbsWTRp0kSjnqenJzw9PfHpp5/C3d0dL168QIkSJTSOlzYeR6VSZRmPsbExevbsiR07duDu3buoVq0anJycpO1OTk4IDg7W+nW+b/r06WjXrh3GjBkjvU4XFxd8/vnnUp33W3SUSmW6+J2cnLBr1y7Y2NjAwsLio2Ii0nUcLE2kQypXroyUlBT89NNPCA0NxbZt27BmzZpM6yckJGDs2LEICAjAf//9h7Nnz+Kff/6Rury+/vprnDt3DmPHjsWVK1fw77//4uDBg1oPln7XV199hR9++AG7du1CcHAwvL29ceXKFXz55ZcAgKVLl+KXX37BnTt3EBISgj179sDW1jbDm0Da2NjAxMQEx44dQ2RkJGJiYjI9b//+/XH48GFs2rRJGiSdZubMmdi6dSvmzJmDmzdv4vbt29i5cyemT5+u1WtzdnZG3bp1MX/+fABAlSpVcPHiRfj7+yMkJAQzZszAP//8o7GPg4MDrl27huDgYERFRSElJQX9+/eHtbU1unfvjtOnT+P+/fsICAjA+PHj8ejRI61iItJ5cg9SIqLcl9EA2zRLly4VdnZ2wsTERLi5uYmtW7cKACI6OloIoTmYOSkpSfTt21fY29sLpVIpypQpI8aOHasxEPrChQuiQ4cOwszMTBQrVkzUrVs33WDnd70/WPp9KpVKzJ49W5QtW1YYGhqKevXqiaNHj0rb161bJ+rXry+KFSsmLCwsRPv27cWlS5ek7XhnsLQQQqxfv17Y29sLPT090bp160zfH5VKJezs7AQAce/evXRxHTt2TLi4uAgTExNhYWEhmjRpItatW5fp65g1a5aoV69euvJffvlFGBkZiQcPHojExEQxZMgQYWlpKYoXLy7GjBkjvL29NfZ7+vSp9P4CECdPnhRCCBEeHi4GDRokrK2thZGRkahUqZIYOXKkiImJyTQmIkpPIYQQ8qZiRERERPJg1xgRERHpLCZCREREpLOYCBEREZHOYiJEREREOouJEBEREeksJkJERESks5gIERERkc5iIkREREQ6i4kQERER6SwmQkRERKSzmAgRERGRzmIiRERERDrr/wANdtvD5cLigwAAAABJRU5ErkJggg==\n"
},
"metadata": {}
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"9/9 [==============================] - 0s 12ms/step\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"from sklearn.metrics import precision_recall_fscore_support\n",
"\n",
"# Calculate precision, recall, F1-score, and support for each model\n",
"\n",
"# Naive Bayes (CountVectorizer)\n",
"precision_nb_cv, recall_nb_cv, f1_nb_cv, _ = precision_recall_fscore_support(test_data['sentiment'], naive_bayes_count_predictions, average=None)\n",
"average_precision_nb_cv = sum(precision_nb_cv) / 2\n",
"average_recall_nb_cv = sum(recall_nb_cv) / 2\n",
"average_f1_nb_cv = sum(f1_nb_cv) / 2\n",
"\n",
"# SVM (CountVectorizer)\n",
"precision_svm_cv, recall_svm_cv, f1_svm_cv, _ = precision_recall_fscore_support(test_data['sentiment'], svm_count_predictions, average=None)\n",
"average_precision_svm_cv = sum(precision_svm_cv) / 2\n",
"average_recall_svm_cv = sum(recall_svm_cv) / 2\n",
"average_f1_svm_cv = sum(f1_svm_cv) / 2\n",
"\n",
"# Naive Bayes (TF-IDF)\n",
"precision_nb_tfidf, recall_nb_tfidf, f1_nb_tfidf, _ = precision_recall_fscore_support(test_data['sentiment'], naive_bayes_tfidf_predictions, average=None)\n",
"average_precision_nb_tfidf = sum(precision_nb_tfidf) / 2\n",
"average_recall_nb_tfidf = sum(recall_nb_tfidf) / 2\n",
"average_f1_nb_tfidf = sum(f1_nb_tfidf) / 2\n",
"\n",
"# SVM (TF-IDF)\n",
"precision_svm_tfidf, recall_svm_tfidf, f1_svm_tfidf, _ = precision_recall_fscore_support(test_data['sentiment'], svm_tfidf_predictions, average=None)\n",
"average_precision_svm_tfidf = sum(precision_svm_tfidf) / 2\n",
"average_recall_svm_tfidf = sum(recall_svm_tfidf) / 2\n",
"average_f1_svm_tfidf = sum(f1_svm_tfidf) / 2\n",
"\n",
"# Custom LSTM-Based Model\n",
"precision_custom, recall_custom, f1_custom, _ = precision_recall_fscore_support(test_data['sentiment'], custom_pred_binary, average=None)\n",
"average_precision_custom = sum(precision_custom) / 2\n",
"average_recall_custom = sum(recall_custom) / 2\n",
"average_f1_custom = sum(f1_custom) / 2\n",
"\n",
"# Print the results\n",
"\n",
"print(\"Model\\t\\t\\tPrecision\\tRecall\\t\\tF1-Score\")\n",
"print(\"-------------------------------------------------\")\n",
"print(\"Naive Bayes (CV)\\t{:.4f}\\t\\t{:.4f}\\t\\t{:.4f}\".format(average_precision_nb_cv, average_recall_nb_cv, average_f1_nb_cv))\n",
"print(\"SVM (CV)\\t\\t{:.4f}\\t\\t{:.4f}\\t\\t{:.4f}\".format(average_precision_svm_cv, average_recall_svm_cv, average_f1_svm_cv))\n",
"print(\"Naive Bayes (TF-IDF)\\t{:.4f}\\t\\t{:.4f}\\t\\t{:.4f}\".format(average_precision_nb_tfidf, average_recall_nb_tfidf, average_f1_nb_tfidf))\n",
"print(\"SVM (TF-IDF)\\t\\t{:.4f}\\t\\t{:.4f}\\t\\t{:.4f}\".format(average_precision_svm_tfidf, average_recall_svm_tfidf, average_f1_svm_tfidf))\n",
"print(\"Custom LSTM-Based\\t{:.4f}\\t\\t{:.4f}\\t\\t{:.4f}\".format(average_precision_custom, average_recall_custom, average_f1_custom))\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "F0yo63vfefvF",
"outputId": "ac459615-95b3-4e3c-c06c-a146615f452f"
},
"execution_count": 10,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Model\t\t\tPrecision\tRecall\t\tF1-Score\n",
"-------------------------------------------------\n",
"Naive Bayes (CV)\t0.9744\t\t0.9746\t\t0.9742\n",
"SVM (CV)\t\t0.9709\t\t0.9710\t\t0.9705\n",
"Naive Bayes (TF-IDF)\t0.9705\t\t0.9708\t\t0.9705\n",
"SVM (TF-IDF)\t\t0.9852\t\t0.9854\t\t0.9852\n",
"Custom LSTM-Based\t0.9633\t\t0.9629\t\t0.9631\n"
]
}
]
},
{
"cell_type": "code",
"source": [],
"metadata": {
"id": "6NqRKPoJfFL_"
},
"execution_count": null,
"outputs": []
}
]
}
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