diff --git a/notebooks/exercises/solution_linear_regression.ipynb b/notebooks/exercises/solution_linear_regression.ipynb index f0d602d0639d88b4018cb62568502fc60b4d859a..20e35d4fabc70cb20d9685cbd5914260304645c7 100644 --- a/notebooks/exercises/solution_linear_regression.ipynb +++ b/notebooks/exercises/solution_linear_regression.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -17,9 +17,10 @@ "import numpy as np\n", "from sklearn.linear_model import LinearRegression\n", "from sklearn.model_selection import train_test_split\n", - "from sklearn.preprocessing import Normalizer\n", + "from sklearn.preprocessing import MinMaxScaler\n", "from sklearn.pipeline import Pipeline\n", - "import matplotlib.pyplot as plt" + "import matplotlib.pyplot as plt\n", + "from sklearn.metrics import mean_squared_error" ] }, { @@ -38,16 +39,16 @@ }, { "cell_type": "code", - "execution_count": 67, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ - "df = pd.read_csv(\"../data/ParisHousing.csv\", sep=',')" + "df = pd.read_csv(\"../data/Paris_Housing/ParisHousing.csv\", sep=',')" ] }, { "cell_type": "code", - "execution_count": 68, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -87,7 +88,7 @@ }, { "cell_type": "code", - "execution_count": 69, + "execution_count": 4, "metadata": { "scrolled": true }, @@ -260,7 +261,7 @@ "4 8435 2429 292 1 4 7055052.0 " ] }, - "execution_count": 69, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -269,6 +270,533 @@ "df.head()" ] }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<AxesSubplot:xlabel='squareMeters'>" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"squareMeters\")[\"price\"].mean().plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<AxesSubplot:xlabel='numberOfRooms'>" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"numberOfRooms\")[\"price\"].mean().plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<AxesSubplot:xlabel='hasYard'>" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"hasYard\")[\"price\"].mean().plot(kind='bar')" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<AxesSubplot:xlabel='floors'>" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"floors\")[\"price\"].mean().plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<AxesSubplot:xlabel='cityCode'>" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"cityCode\")[\"price\"].mean().plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<AxesSubplot:xlabel='cityPartRange'>" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"cityPartRange\")[\"price\"].mean().plot(kind='bar')" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<AxesSubplot:xlabel='numPrevOwners'>" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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rPjnJTklW9pNMzWU8JMmpSZ5IN/nVP8zb90eA6SR7JTk+ySv6+5yS5MR++e1JPrqxx9pvs1eS05KsSXJOkn372z+d5N/7SYX+Mcnz+98S1vaPeeex/oPoQcGi1iTsDRxfVU+mm9T9TxbZ/inAq4BnAh8Ffl1VTwPOA968wPYvp5uXeM7N1b2xw3eAo4HD+q9ngPf3tx+UZMd++z+lm/FtP7p5pe+e21G/vBZ4MnAO3QxtAI/tt6e/7exFHutq4N1V9QzgA3TTks7ZA3hOVb2/X/eu/jeF5wG/2cT3Sdsoi1qTcN2860vX0L0Rw6acWVW393NO/xL4Rn/7ZRvc95+SrAVWAUfOu/0/+8/PoivTc/vt3gI8vqruopto/+X9cMMRwNdGeBznAM9Lsh9wBd1UuLsDz+beFzX8v8faT8X6HLqpQNfSDdPsPm+/J8/74XAucFy6dy7Ztc8q3YdjZJqE+VO13k33DjV3ce+JwUM3sf09876+h/s+Rz9YVV9e4Hi/6j8HOKOqXr/ANl8EjqKbs3imqm5PcgVwQJIl/TzcJFlC91ZsV1TVDf10nivpzqAfCbwWuKO//6M28liXALf2Z8kLmctLVR2T5Jt0byt1bpIXb6mpO9Uuz6g1lPXc+2YIr57QMc4HDu7HnkmyY/9uLADfA54OvJN+ovuqupruba6OnrePo+neduvqeft8H11Rn0M3VHHOpkL078xzXZLX9DmSZP+Ftk2yV1Vd1k9CfyGw72Y9Ym0TLGoN5Z+Bv0hyMbB8Egfoh07eCpzUT5pzHn3x9UMNp9K9efCp8+52JLBPf2neNcA+3HdY5RxgWV/cF9GdVW+yqHtvBI5Mcgmwjm7e4oW8L8nlfd47gW+N8li1bfEl5JLUOM+oJalxFrUkNc6ilqTGWdSS1DiLWpIaZ1FLUuMsaklqnEUtSY37P4x0EI9PFqfDAAAAAElFTkSuQmCC", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"numPrevOwners\")[\"price\"].mean().plot(kind='bar')" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<AxesSubplot:xlabel='made'>" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"made\")[\"price\"].mean().plot(kind='bar')" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<AxesSubplot:xlabel='isNewBuilt'>" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"hasStormProtector\")[\"price\"].mean().plot(kind='bar')" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<AxesSubplot:xlabel='basement'>" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"basement\")[\"price\"].mean().plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<AxesSubplot:xlabel='attic'>" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"attic\")[\"price\"].mean().plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<AxesSubplot:xlabel='garage'>" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"garage\")[\"price\"].mean().plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "<AxesSubplot:xlabel='hasStorageRoom'>" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"hasStorageRoom\")[\"price\"].mean().plot(kind='bar')" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<AxesSubplot:xlabel='hasGuestRoom'>" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"hasGuestRoom\")[\"price\"].mean().plot(kind='bar')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Since our approach from the example with plotting the data isn't working on the 10.000 datapoints. We take a new approach where we also look at the correlation but with a correlation calculation." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "price 1.000000\n", + "squareMeters 0.999999\n", + "numPrevOwners 0.016619\n", + "numberOfRooms 0.009591\n", + "cityPartRange 0.008813\n", + "hasStormProtector 0.007496\n", + "floors 0.001654\n", + "attic -0.000600\n", + "hasGuestRoom -0.000644\n", + "cityCode -0.001539\n", + "hasStorageRoom -0.003485\n", + "basement -0.003967\n", + "hasPool -0.005070\n", + "hasYard -0.006119\n", + "made -0.007210\n", + "isNewBuilt -0.010643\n", + "garage -0.017229\n", + "Name: price, dtype: float64" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "correlation = df.corr(method = 'pearson')\n", + "correlation['price'].sort_values(ascending = False)" + ] + }, { "cell_type": "markdown", "metadata": { @@ -277,17 +805,20 @@ } }, "source": [ + "As we can see some of our features got no relation to the price variable, so we won't stick with them.\n", "We are separating our dataframe in the independent X variables and our dependent y variable." ] }, { "cell_type": "code", - "execution_count": 70, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ + "features = [\"squareMeters\",\"numberOfRooms\",\"floors\",\"cityPartRange\",\"numPrevOwners\",\"hasStormProtector\"]\n", "df_y = np.array(df[\"price\"])\n", - "df_X = df.drop('price', axis=1)" + "df_X = np.array(df.drop('price', axis=1))\n", + "df_X = df[features]" ] }, { @@ -299,18 +830,18 @@ }, "source": [ "The train_test_split function is necessary to separate our data in two parts. The training data, which\n", - "contains 80% of the data, due to our test_size=0.2 parameter, is there for training our model. The test data\n", + "contains 90% of the data, due to our test_size=0.1 parameter, is there for training our model. The test data\n", "is there to take a look at the performance of our algorithm to unknown data. We need to get an accuracy score from our\n", "unknown test data to make sure our algorithm isn't overfitting on the training data." ] }, { "cell_type": "code", - "execution_count": 71, + "execution_count": 22, "metadata": {}, "outputs": [], "source": [ - "X_train, X_test, y_train, y_test = train_test_split(df_X,df_y, test_size=0.2,random_state=42)" + "X_train, X_test, y_train, y_test = train_test_split(df_X,df_y, test_size=0.1,random_state=42)" ] }, { @@ -321,25 +852,25 @@ } }, "source": [ - "The next step is to scale our data. For that we are going to use the Normalizer() function, so our data gets normalized between 0 and 1.\n", + "The next step is to scale our data. For that we are going to use the MinMaxScaler() function, so our data gets scaled between 0 and 1.\n", "The advantage of that procedure is that our different columns are getting weighted equally.\n", "We only take one transformer, so we don't need a pipeline for that, but it makes adding additional transformers later easier." ] }, { "cell_type": "code", - "execution_count": 72, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "pipeline = Pipeline([\n", - " ('normalizer', Normalizer()),\n", + " ('minmax', MinMaxScaler()),\n", "])" ] }, { "cell_type": "code", - "execution_count": 73, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ @@ -360,16 +891,7 @@ }, { "cell_type": "code", - "execution_count": 74, - "metadata": {}, - "outputs": [], - "source": [ - "model = LinearRegression()" - ] - }, - { - "cell_type": "code", - "execution_count": 75, + "execution_count": 25, "metadata": {}, "outputs": [ { @@ -378,32 +900,36 @@ "LinearRegression()" ] }, - "execution_count": 75, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ + "model = LinearRegression()\n", "model.fit(housing_price_train,y_train)" ] }, { "cell_type": "code", - "execution_count": 76, + "execution_count": 26, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "0.7583914568829306\n" + "Accuracy : 0.9999986486785046\n", + "Root mean squared error : 3416.711042257042\n" ] } ], "source": [ "predictions = model.predict(housing_price_test)\n", "acc = model.score(housing_price_test,y_test)\n", - "print(acc)" + "print(\"Accuracy : \",acc)\n", + "rmse = np.sqrt(mean_squared_error(y_test,predictions))\n", + "print(\"Root mean squared error : \", rmse)" ] }, { @@ -414,28 +940,22 @@ } }, "source": [ - "Finally we are plotting some datapoint examples to get a visual understanding and see what an accuracy of 76% approximately means." + "Finally we are plotting some datapoint examples to get a visual understanding and see what an accuracy of nearly 100% approximately means." ] }, { "cell_type": "code", - "execution_count": 77, + "execution_count": 27, "metadata": { "pycharm": { "name": "#%%\n" - } + }, + "scrolled": true }, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.7583914568829306\n" - ] - }, { "data": { - "image/png": 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", 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xo5hnxoiKIJZaDfG5WGripcS0PhIIdOeoe9ZuZlbakC3I/DAnzzGhdGGzO5c+GJhY8zq2FY8wNdqaGHonIDLjpHFhd3oWPW7rjfeQxkX5+NXVTCAVVR9Uwt21xJEqisnE+bW/xK7CC4ye7ZyaGIvhz5xhwjZ4xfZ1d/4qAOd+/KXWGtQgjvwECfP835u9Jl7KRPWhTtSdoxaKiVFLazI/fLPnidoWnwnOpf82Nfxx1gh/XMQyO0VcWfq132KxctJ9gA3JX1xVzQRSUVWxupB8fD4G7/sgVSm48C+d3/1FViv0ly6Q9W66Yl//hus4atlB7/lv6ibWOxdfcYrsAvn/nrCaspfXiTpRd44aIOneRE9hSNNzyGqV3vIos57Bhj+zdssezpoG8Z37Z+0M6zBcxWlmLOGGjq1uvp8QKc6+9AuNrWod2bp83L9weuLl9KzZxGHHfjaMfoNyqaSVaS1hYvh0LeNj/vBhestbWVcd5szL/9piyxZHVquEq1GKrvmzlfwRdQJXSumjG7kuHXUlvI0ICZJR7ToBx6ZG1K4kwStnAosxteYBrisdZWL4jEaWdRa+coy8vbHX/o23vJmqFESvomYChaR6j7pDC6cnzkdlz3voJsbhn+lbFLIU9RofczM+5rLt7vdQlGaiv9CXpDwZm1Dz/33zZyt5/UGK0gw6kZHr0lG/kvnxvGbnmK6l5jn7ti7rcwO3/woAQ098pek2dRrVSoWQTFBxN/baH+rq46RlG6GrqJlAZUZ11L7I8hz1zrvfQRwvlYP6cmDLpV7jo2/Tnnn3+0NdHHbdwuapH1AuFVto2eLUxS624PyhT6EoxIUfk05k5Lp01N21Lz09fFizc2TG1IWc8Nrty/rcwKZdnDZtxH/u6q1d0Sjx6DgWUUF45i9GNO9n+u9kc/kUsYmrJB89O01OWq8o8boUFqudk71vZHf2X5nu4Nx8c+wE0wTwhxZ5q7r+HYRIcuwX+nmTykwNAeDqGlzwmLQ5iL1gpOctSFf/RjLSAVPaZX5UoqcoSjPda5YX+gCIrn2AbeXjjA2d0MCyziE5oXZusQYWLkZ0OV0Xmwl8QwuTWo55dpqk8F1R4rUR+u/6IBZR4fQPO1ep6M2cvVjjYyF23Pk2krgpPK+fEgzFmtgl2De44DFZawhnSR95/7p01EJRGLOsxZ0+rdk5bKkhxky9mMzmZX927avU8Mf5n+nnxmsH2ZiaY+oMNe6oN+68mUmCmE5f0c2tI7EW48w0IB+fjzVb9nDcsp3+c1/XZVbEUshqhYHSeTLeK5tuzMVmc3AidC87Uk+QTetDll1NjVKUZkKRhe/doj2Cv6IPe3XpqAFSnk30Foc0Gz+Qv0DCvriabiH6NmzntHkTwfPXdvgjX+uA4etefEY1F6EoDAVuZ3PmIKViXivTWoarFGd2gVrcjZDZ8SuslaMcfbrzHlyTtYwPFsj4mIv3pnfjEEWO/lgfazuWzBjTSgjFZFrwmKozgl+mqJTLLbRsfnTrqKvhbYRIEZtqfsJ5pVymrzJO3rd+6YMXILru9Wwtn7xqRAsroa5KDHU3nosOYL7utbhFjpPPdH4zAV8lQdG+cke94973kcFB9qkvNtGq1jBZq/HhXbNzyWO37b+HEdGD45g+JOWu/ARJy+LZSoqnG5OQJHQgetGto3bWvvzx082v+TE5fBqrKGMKL/7Kthjr7ngXAOd/ro8ZQjtQshPE8GGx2pb1ua23vIGCtJDp8GYC1UoFv0xTcTaWRz4fDreXY6HXsDP5OKmEfspqNkJ+ZPGMj7kIRWF44I1szx/ShbLXX5pm1r547rvFp+5P6aANn24ddc/GvQBkNKj5ET2v3mDu/m0rHqN33VZOmrcQOf/dZpnVcdhyUyRNy59Nuj0+jjuup3+qs5sJpOJTmEW1Yfn4QgRf9QG1+8sPO6unohI7QRQ//nBj6ZkDr36fquz9cXvfHirlMmEZo+xePKXSEVT3z+qgya1uHXW4dx1pnIjp5md+zI6r2Rpdg8tLzbucxODr2Vw5zfCZI80wq+NwF6fJWFc2m5xddy8DcoyxM9qlYGpNuiYfN3sbl4/Px8brX8U50yChE48ipWyGaS3Bt0CNj4VYs2kXJ8zb6D73Te2MaoD45DBmUUVZQOxSx3tRRt5+daJuHbWa+TGIR4PMDxE/Q0Y6CHUt/kUtxWAt/DH8s2uz9oe/EqPgWNlscs1NDwIw8nTnKvNmYupMy+5fnaNGCKKb38GWyilOv/RUEyzTnlcyPpaX3prc/Eusrw5x5uX2/T/j4zWxS3jxZAJ/LSOkktZOId0ounXUAGnPRnpL55ueuuSYGWLc3L+i3Ne5dK/dzAnLdXQNX3vhj1KxQFCmqLoar3Exl4EN1zEkBnBe+HGTLWsd+VSt+3hwearE+dj6mg9QkBamf9YZOdWTI2fUGh+RpTM+5rLlnvdRkiam2ygpz06rOdSersWTCVweH1lph4zhqBdFRrYRYIbo5EhTxw0Xhkk5G08pW4zk+tezqXKW8yevzn6ACxGbHEEREsXbuCrxcsa67mBL7kXd5NYul3KqLh9vPI98IbzBLk4499ITP7jqsVrBVK3Gh7uBjI+5BMI9HHbdxIaJ77Ut7a0YVx11uH/prK+EEsCsgya3unbU7gG10MvE6UNNG7OQn6WnOkXJv6Ep4214tRr+GP3FtRX+SE2pN7s1uPLwkWf3G7CKCqee7NBmAtkpStKEN9BY04ClyDn7CVQ7I/NjdvQoAP2b9y77s3LX2+kiztF2NZFIjZCVNrz+pddXZsxBHDqQkevaUXfXboJME2t+TJw7hiIklq6Vp+bNJdK/geOW7XQPf68p43UK2dpCmju8cke9df+9pKWTUoc2EzBloySFd1HRxHKQnj4CzDCbnWnKeFpiih5fVsbHXLbf+XbSOMk/157JjS07TtQUaSj0mbOGcJfbLyPXtaMOdQ2QxI0SbV7mR3xYHcs3sLzY2mKkN76BjdUhzh3Xvs+jXiglVUft716ZuhPUbtUnPQdYn/gFstp5zQQshRhp08rk4/NhrtVMiY4NNW1MrfBlzjBhHVzRZ+0OF8eD97Aj+VNmM6nmGtYArsIk6SXELnVKjjD+quGoF0UoCuPWQbwzzcv8KEyoqXnd63c0bcwNr34XVSkY/9drp/ZHNT1OWSoEw6tbSKtsuo8wSc7qrLB8IzhLcbKWYNPGs4dUhWd68nzTxtQCWa3SX7pAxrf8gmZ13AfejVMUOPLj1v/OBMtT5ByNLYJXXV34yFLIt7drvK4dNcCMZxP9xeZlfiiJM8Tw4fWvXPZ7OeHeQU7YdtI78r2OyoNdDabsJHHhR1lBUau5bLjlwY5tJuAtJyjYmncf+boHAcjF9NFQdSGmRk7jEnlYZsbHXLbdeB/jIoLt6N830bKlKRbyBGWKiqexBWDFqzr0xHR7RS+r+y1rBZFteGPfYHL8PN0NrNIuhTtzgSnLAM379VKZ2fhGrjv2B5w9dpAN22+kXKmSnc2TzabIZ1Lks2mKsymKszOUczNU8jNUCjNQyEAxA8UspnIO903vYe9tr22ydc3Hnp8iaQ6zOk0eRLoHOG7ZSnD0J80wq2XIahW/TDLkWLl8/HLCvYMAlJPNzXJqNpNnXqQb8K5Z+VupYjJxvv8N3Dj8JaJj5wn3NScLaymiY0P0CYnJ39jais2nZjWlp0fpWUFJ5Gahe0ftXrsLjsPk6UNNcdRdpWHO+m9tgmWXsvHOX6Z69A8JPPoWEoCTPD5Rwtfg52exY5VFXvzXNHSAo/YUp0nZV5+WBhDru5PbLnyW+OQwwWUWeGoXmZkkHlECd3MyPkCt+5HChZhpv2R5MS52dVlBxsdc+u54P6b/+0VO//hLhN/9iWaYtiSpiXP0AY4lxC51nEHVUefaLCPXvaPu3bQXHoPsyGHgLasaayYVJ0ySU8vsk9gIoe61HNz671GmjyAtLqTFDTY3is2NYvdgcXgwO7xYnR7sLh92lxeH24fN6UFYXDgVhcN/eCfuQvuT6xshUI0x5djXlLEie98IFz7L2Se/QfDBDzdlTK1JTo/iAUyeVaoSLyOuhLHN6qPz9UKYomqNj3B4ZWKnOmu37OGkeQvhc98EWuOos9Nq/N9bCzMthbeWI19os4xc94460NVPAi9KdPXlRCfOHcED2Lq3rN6wedj/K6u72XKOXrqS+pcQ53NZ/GSQy2jBtRibdt/K1DeDKKd/CHSGo87W5OO2ZXQfb4QZaxfugj769C2EL3OaCesgzQj6JDY+yE0n/htnjz7Lhu03NmHExSkl1Ph/uL8xHUWg1guzOtPeCZTuFxMBxqyD+GZW3/U7NaKm5gXXNi81r5lUPH2EZYJCQd8F9WPj6s1u8jXHUSsmhXP+W9mSeYZyhzQTyCXVWa8r0FxHnXf2EKi0X2CxEM3I+JjL5rvfR1kqTP7sr5sy3lIoM2OkcOFqsMelze4kiRuRbe/DsyMcdda3mf7S0KozP0pTp6hKQc+gPh21KbAGRUiiY/pOz0rXaiXYl9ErcSnM170ONzlOPfvDpo2pJcW6fDzcvGsAUHX3EiZJoZBr6rjNYmrkTC3jY+UlgucS7B7giPNGNox/l0pF+1x62+w4MWV56wpJJYClzTLyjnDURLbhETkmRlY3q7YkzzKphLE7XE0yrLk4wurKd3LibJstWZzZmJqV4I40b+Fvyy2vpyjNpDukmUB1Rp1h+SPNeauoY/Krjj+m087kk7UaH410dWmU8q63002MY09qX9zMU5ggbVveukLWHMRRNBz1knjWqjU/ps68uKpxvLMXiFr1m1VQX+CoL3jolWJCjc8Ge1auSrwcjzfACdtOItNPNm1MLVFmp0ngwWyxNnXcuuglOTHU1HGbRa6W8dG7yoyPuey4851kpIPZg9pLykOVaQrO5T1cc7Yw3jbLyBty1EIIvxDi60KI40KIY0KIW7Q2bC79m9XsgtmRldf8kNUqPaURZj2DTbKq+URqCxyVhL4FD2TGKUoz3sBqs6gvZabnZgbL50nH9b2YBmDJx0gp/qaPW28UnI3q8x5QahkfgVVmfMzF7nRzLHAX2xOPk9OwzkkuO1NbBF9euKrsjOCvJrUxqkEanVH/GfB9KeU24Hqg+W1XFsEb6iaGH1PsxIrHiE2P4RWzyFD7ktaXwuH2qXm06fb3aFsMc3aSmBJcdT3vy/FuuxNFSM49p/84taMYI2tunny8TrBXfViXE/oUvXgzZ5i0Nl+c4jrwLtwix5HHv9r0setMj6qhU1NgmYXEXF24RJ7sTLL5RjXIkr9pQggfcAfwfwCklEUpZVJju65gwjaIL7Pymh9T59RXNmfP1maZpAkxUxf22fa3/lkMR36KlLl5irw6m/a+mry0kD/906aP3Ww85QT5JsrH67i9AbVYvQ5FL/WMj5lldnVphG03vY5JQpiPaCcpT02oIUVneHkPGlOt1Vpyun0TqEamROuBaeCLQogXhBBfEEJcsRonhPigEOKgEOLg9PR00w3NeDcxULpAdYUrw9kxNQ87tK55xZi0YMbajUfnohdvKcqsrXmKvDp2h5PTtusIR/VfPN9XTVKyN99RIwRRUxhrVn8P66mRM7hFDrqanzWlmEwMRe5iy+whyqVi08cHyMVUR+2vSfUbxeZXY9ozOnfUZmAf8L+llHuBLPDQ5QdJKT8vpdwvpdwfiTT/l1jp3o5L5Bm/sLJZdXn6NEVpomdtc+pQa0XB1Uuo2vwHXTMJVuMUnc1V5NWZ6TrA+vJZ0kn95hLnc1k8Igeu5sbo68xYIrh0KHqZPKsu5nuamPExF/O6m3GKAkPHtHlQV2rhpHDf8kpRuEJqTHs20b63nEYc9QgwIqV8uvbvr6M67pbiWbsbgKkzK6v5bE+fZdzUi2mV1d60puodwE+GzEzr6/Q2wkwqrs6q3M0VetTxbLsLRUiGnvuRJuM3g8SU+guveLRx1DlHD4Gy/h7Wudpi/mprfCxE385XARA9/nNNxjfNjBLDh83uXNbn6q3WSqn2veku6aillBPAsBCiHty9BziqqVXz0LdFvTlyY0dW9Hl/bpiEvXnpZFphqS10REf1mUsdn1SzEcz+1Td0nY+Ne++kKM3MnnpCk/GbwUxMDUtYmywfr1Nx9xKSCUoahQBWihI9SQxfUzM+5tKzdgsxfCijz2kyvj03Qdy0/IdrINxLRQpkG2XkjS7bfxj4ihDiJWAP8AeaWbQAXn+YaYJYVpD5UalU6KuMkfeuvvqe1jgj6kJHauJcmy2Zn5kp1VE7VtErcTEcLjenrdsIRp/VZPxmMJtQ5ePOJsvH6yi+fsyiSqzJTZ1XizdzmvEVdnVpBKEoDDt30JN+WZPxvcVJMvblh+xMZjNJ4UOZbV84qiFHLaU8VIs/75ZSPiilbEvb6An7IP7M8tWJk8OnsYkSSli/qXl1ArX0rHxMn8q0XC3O5+3STjiU6jrAhtJpMun2t0Caj2Ktzocn1FxVYh09il4u1vjQIONjLvnufayVoySjzZ29ymqVyArELnWSpgDWfPvWTTpCmVhn1ruZ/vLwsmsCRM+rkRp3X3PqE2hJuHeQqhRUdSp6KdfKPQaaqEq8HPfWV2MWVc4+9y+anWM11OXjgUhz63zUcXepb1WzUf08rKfGzuIWOUSTanwshHezqqU7//LPmjpuOhVXa5T4VvadZS0hnMX2dYjvKEetdF+HUxQYH1pe+GN2XD2+a1DfqXkAZquNmAhgyugvjxZAzIwzK224Pc1r6no5G/fdRUma9Bunzk6TkQ7sTrcmw4dq6WPFuH5CH5OnDwG1Rh4aMrjrNipSMHumuaUE4mPqm7glsLI3wYItjLfclkAC0GGO2jd4PQBTZ5eZ+RE7TVbaCfXot87HXBLmCI6c/vJoASyzk8SUEAih2Tmcbh9nLFsITD2j2TlWgyUfJamBfLyON9BFXlqQOlKoXuzqsmmPpudxegKcN6/DFT3U1HHrDYNdkZWpKsvOLoIy0bTerculoxx1/+Y9ABRGl5f54ZwZYtzc33TJs1Zk7D34ivrLowVwFKZJW5qvSrycRNcBNpROMZvRX5qivRBjxqzdG4VQFGJKCEtWP51eTNMn1IyPJlcLnI+obzeDuWMrFrfNR33Nx9+7soQC4Y5gFWXSyfaEPzrDc9VweYNMEMa8zMyPYGGYlFP/qXl1Su4+ItXptj29F8NXjpKza5M/PBfXlldjERXOPP9jzc+1XFzlODmrBqrEOaQsXbjy+lGoejNnNM34mItYcwCvyHLh1EtNG7OaHKEiBeEVrq2YfWqGT3KqPWtHHeWoAabs6wnMNp5jXCjk6K1OUvI11npHF3j7cYgiiZh+flFBXTkPVeOUXdqoEueyYd/dlKVC5oT+6n5oJh+fQ87ejU8nohdZrdJXOk/Gu7El5+veoQpfpo42T/hizowRFcEVl6W1B2oy8lh71o46zlHn/JsZKA9TLpUaOn5i6DgmITF36Vs6PhdrSI2jxXQmekklothFCaGRKnEubm+As5ZN+KeeXvrgFlIuFfHJDFVn88skzKXk7iVcjTX19X+lTI2dwyNyiEhrOiOt2bSLNC7kSPNy6Z25CRKWlb8Jemoy8nyiPWtHHeeole7t2EWJsaHGKq3GL6iped4Bfbbfmg9P1yAAM9NDbbXjcuK1BRlLE1twLXq+yI1sLJ7QtEbxcklOj6MIqZl8vI7i7cMqKsTaWAiozlQ940OjGh+XIxQT5+3XEU42L/ThK02RXWZnl7kEIqrAq5xuz7pBxzlq/zo1PSh6trFuL/mJkwB0r9d/al6dQN8gAEWdiV4y02q6mDPUGkft3PxqrKLCmRceb8n5GiEVVR2n1adt+Md6UfTS/m4/2VG1xkevxhkfl5wzspfByhAz6dWnxMlqlXA1Ssm98vvWEwhTlCbkTHsW+fVdoWge+rfsASA/2li3FyV+hjheggFtX1WbSTDST1GakSn95NEC5Gt5vd5IaxZm1++7l8pPBTPHfwq3v6kl51yKbE0+7tCozkcdd+0ap6OjnDt3jny+fd3Z7Zvu5vCGWzHFUkzGWpOF49j3y5zcfh/FM+ew2lc3i61Uyphe+xXsFh/Hjq2850nltV/DoVhXNQaA3W5nYGAAi8XS8Gc6zlE73X7GRRfWxMmGjndnh5iyDND8XhzaIRQT00oIi85EL5Vk83slLobHH+KUZSNeHcWpCzX5uCukTVGqOoGa6EXYQ3g8HgYHBxEa5q4vRn7sGFIIHL2tU/ZWyiVMU4fJWLtwr7LTe352BnuyTNa1Fpdv5YvA+TFJVZhw9q68+YiUklgsxsjICOvXN54q2HGhD1AzP4LZxmp+RIqjzLia3zpIa1KWbpw6Ss8CENkJUrg0U+TNRyx0I5sKx8nnsi0752JUahXU/BrJx+sEwv2UpAnF6iAUCrXNSUspscgiFZOtpec1mS0UsKCUVv+9V2pVCE2rbERcVcwocnWLu0IIQqHQst+QOtJR5/xbGKiMLlkGMjOTpIs4lUAHpebVmHX0Eijpy1FbZ6dIKNqmpV2OY/Md2ESJ0y/oQ04uM9MUpAW3x6/peRSTiagSBFltm5MGNcvFJKpgtrf+3CYHVplHSrmqcWRZ9RNmy+oeNlKYMVFe1RjAir7PjnTU5p7rsIoyo2cWVyhOnFX327q3tMKsplJ29xKR8YbTEFuBqzjNjFV7VeJcBm+4j6oUzBzXh/DFnIuSEP6WqFxT5ghilTO41TI9Oc5ffulrmKxqsf2f/OQnvOENb5j32A984AMcPdpYqfrPfvazfPnLX178IIsLMxUOPvs03/3ud5dld51kMslffeH/UJUCk7nxmPB8SMWCWVZW/eBYCR3pqP3r1G4vsXOLZ34kR9Sgv3/Nds1tajZKYA1mUWV6Qj+ZH75yjEILVImXnDMQYcg8iGdCH3U/bIUYaQ3l43PJ2rtRZHvVqYnoJH/55b/HYnMseewXvvAFtm9v7HftQx/6EO9973sXPcZsV0Nszx98dnWO+otfpixMq38zMZkRAsrl1k+eOtJRD2zZQ1UKCkt0eylNngKgd33nOWp7SF2wS47ro4FApVIhJBOUXdqLXS5nOnQjGwtHyedzLT/35bhKcWYtrVmaLrl6MdGeGVydT/zef+XM+RH233iA3/7t3wYgk8nwtre9jW3btvGud73ron133nknBw8epFKp8P73v5+dO3eya9cu/uRP/uSKcT/5yU/yx3/8xwD8+Z//Odu3b2f37t28853vvHiM1eEkVyjz+3/wMI8++ih79uzh0UcfJZvN8mu/9mscOHCAvXv38s1vfhOAI0eOcODAAfbs2cPu3bs5deoUDz30EOfOX2D/fW+/aP9KUUzqjLzShs47HZf1AWB3ehhVurElFq/5YU6eYYIIPS1c/GoW3u5BALLT7c+jBYhPjxERFRRP6x21bdMdOKa+xpFDT7Dj5vtbfv65eCpJ4rYWiae8fQgklXIZs8XC7337CEfH0k09xfY+L59448Iag9//2G9x7PgJDh06BKihjxdeeIEjR47Q19fHbbfdxi9+8Qtuv/32i585dOgQo6OjHD6sptAmk8lFbXj44Yc5d+4cNpvtkmOFUMDu4eP/4Td48cw4//N//k8Afud3foe7776bRx55hGQyyYEDB7j33nv57Gc/y0c/+lHe9a53USwWqVQqPPzww7x86CBP/ss/4+pZnQRe1Bx1tWLMqBtm2rGB0BI1P3yz54natGkZpTWhPvWmKsX1EfpI1kIwFo1acC3G+n33ApA69pOWn3su1UqFgExRcbUmTm+r9c8slwotOd/lSCmxUERe5iYOHDjAwMAAiqKwZ88ehoaGLtm/YcMGzp49y4c//GG+//3v4/V6Fz3P7t27ede73sXf/u3fYr6s+XTF7MRE+ZK3iscee4yHH36YPXv2cOedd5LP57lw4QK33HILf/AHf8BnPvMZzp8/j8PhQEqJAKRpdfFpAJNZzRqRbQh9dOSMGiAf2EL/yNMUCjls88TPZLVKT3mU4/7XtMG61ePxh8jgQOikJnEmqlYNc4da76h94V7OKetwT7Q3nzqdmMYvKuBqTZzeGVlLtVSmWstaWGzmqwXlUhET8ora4zbbK9kTJpOJcvnSTIhAIMCLL77ID37wAz772c/yta99jUceeWTB83znO9/hiSee4Nvf/jaf/vSnefnlly86bMXmQkHNq64jpeQf/uEf2Lr10nzm6667jptuuonvfOc7PPDAA3zuc59jzUAtjdK0utQ8AFNNoCKNGXXjWHquwyIqjJ6ZX6EYj07gJYsMtqbilxZElQjWrD5EL4Wk+sDwdbenXOx0aD8b84cpFtozuwRI1epumDWWj9cJ9KiCiLqjbjWlwiwel5NMdnm5zNFolGq1ylvf+lZ+//d/n+eff37BY6vVKsPDw9x111185jOfIZVKkclkLu63Otx43C7SqVek5Pfffz9/8Rd/cXGW/cILaiORs2fPsmHDBj7ykY/w5je/mZdeegmH3cZMJotiboKjNpmpSAHV1afoLZeOddSBWreX+Ln5C7dMDakLjfZVqIjaTdrajaegj1zqakpV5AW72hNKsmx8FS5R4MyLzSt9uVxm4mrlNHuLHHWoZw0SoA0zOIBqMUco6Oe2W29j586dDS/GjY6Ocuedd7Jnzx7e/e5384d/+IcLHlupVHj3u9/Nrl272Lt3Lx/5yEfw+/0X95stNm679WZOHD9xcTHxd3/3dymVSuzevZsdO3bwu7/7uwB87WtfY+fOnezZs4fDhw/z3ve+l4DPzW037uHGW25f9WIiQEWYEVUj9NEw/Zt3U5GC0vj8eZszI8cBCK/tvIyPOnlnD/3xxqTyWmPKThDDR8jaWoVancF998FTkDj2OBy4py025C92H9dWPl7HZLZQxdQWxwAgynnKmPi7r371ku133nnnxZ/rC3ygLjTWWWwWDWrWR52f/3zxh68n1MOT3/0K1r5X+jV+7nOfu+K4hx56iIceeuiSbZnYGP/3f/0B5a6dmFeZRw1QESYUacyoG8ZmdzGu9GJdIPOjEj1FSZroXtt5Ypc6Ve8AIVLkZtsvn7blpkiaWqtKnEuga4Dzyhpc40+1zYZyWn278a6y9sRyqAqlbY5aqRYoidWHDFaNxYmVMqXiCsJelSIVKTCZmjMnlWL1MvKV0LGOGiDqXE9kgcwPW+oc46aeFXd00ANmvxpmmNZBAwFXcZpsi1WJlzMVvIGNucNLlg7QCpmZpiwVfMHWiX4kJkyy9Y5aSom1DTU+5sNUE74Uc8uvSy6qJcrC3DQZflVpjox8uXS0o84HttJXHSefm71inz93gbi9c/okzocjrBaTSk0MtdcQIFCJUXC0Jja7EOYNr8Itcpx+6cm2nN80O01SeFFMppadUyqmtsiW1YyP9tT4uByrw01VCmRh+W+WpmqJilh9yOMiigUzVaot7mfa0Y7a2rsds6gycvrSBcVqpUJfZZSCd7A9hjWJQK9aTGo22l7RS7FQIChTVNqgSpzL2n1qqmX8aHvqfljzMVKm1sjHLyJMmES15S25SgV18mOyLi0d1xpFUSgqNkyV5StTTZSRSvMctVDUEEqlxZk4He2og+vVzI/E0KWOenL0rNrbL7ypHWY1jVD/IACVRHs6H9eJTY2gCInJ19tWO0I9axlR+nCOtSdO7SzFyLZIPl5H1GbvrRa9VIuqU7TYnC0970KUTQ5s1fyyZrLValV9G2mmozbXZeStDUd1tKPu27CLslQoTVya+RE9r/7b3de6QudaYLO7iOHDNNNe0UtqSlUl2lrUK3ExJvw3sHH2pbZUFXRXkhStLXbUbZrB1TM+9LLGo9hcKEJSzDce/iiXCggBogk51BftqAlnWi0j72hHbbU7GDP1Yb+s20t2TM0E6VrXOX0SFyJhjmDPtafzcZ3ZqNqCyxVpvxzftOF2vGKWM4dbq1KU1SqBapKyxt3HL0epZSvIVr9q1zI+kskkf/mXf3lxe0vLnM7BYvcAUF6Go64XT7pc7DK3INTHP/5xfvSjHy04xqFDhy6p3Pfd7/+Ah//nF1vuqDs2j7pOzLmBSPb0Jdtk7DSz0kaot/M6u1xOxtaNL9fe0Ecxoaoj/W1SJc5lzd774OB/Jnbkx7D39qU/0CQyM0k8ogiudjjqSktly/WMj5zJe9FR/8Zv/MaSn/vCF77Q8Dk+9KEPLcsmi9VGGROiOL+jllIipUSZUye8WlbDRcoiDQM+9alPLXreQ4cOcfDgQR544AEAHnzLW1Bu2UjGmFEvj2JgK/3VcXLZV2SnjvQ5xs39LSnurjUFVz+RynRbS11WZ8YpS4VAi4QeixHu38iY6ME22to4dWpafViZPK3NfBFCUMYEldbNqC9mfFjsPPTQQ5w5c4Y9e/a0vMxpnS996Uu8+cEHufttv871t9zN7/3e7wEwNDTE1q1bee9738vOnTsZHh7mj/7oj7jxxhvZvXs3v/9pVRFpsVj59Kc/zZYtW7j99ts5ceIV7cX73/9+vv71rwPw7LPPcuutt3L99ddz4MABUqkUH//4xy8psfrlL/8Nv/FfPgPVMkNDQ9x9993s3r2be+65hwsXLlwc8yMf+Qi33norGzZsuDj+auj4GbW1bzvKsGTk1Its3nMbAOHCMJOuzpWOX4K3H/dUjlQyji/QHsGJKTtBXAToMuvjdhnz72NT/AnK5fIV1da0oi4ft/lbn6JYxoxSLcP3HoKJl5s7eM8ueN3Dl2wqFWaxoGZ8PPzwwxw+fLgtZU7n8swzz/DUT39Il2mGG9/0AV7/+tcTDoc5deoUf/3Xf83NN9/MY489xqlTp3jmmWeQUvLA/ffy+FMv4F1X5atf/SqHDh2iXC6zb98+brjhhkvGLxaLvOMd7+DRRx/lxhtvJJ1O43Q6+dSnPsXBgwcvKjC/9KUvIRGIaokPf/j/5X3vex/ve9/7eOSRR/jIRz7CN77xDQDGx8f5+c9/zvHjx3nTm97E2972tsa+jwXo+ClncP0eABLn1cyPYqFAT3WSkr/xDr96xhJUww3R0dNLHKkdjtw0KXP7VImXo6y/Hb/IcPbowZadM5dQHbUr2PrMl6pibqnoZamMj1aWOa1z33330dW3BofDzhvf8MBF2fm6deu4+eabAbX86WOPPcbevXvZt28fp06f4cS5EX72s5/xlre8BafTidfr5U1vetMV4584cYLe3l5uvPFGALxe74K2SBQUWebJJ5/kV37lVwB4z3vec4kU/sEHH0RRFLZv387k5Orr9ehjirQK+jfsoChNlGuZH+Pnj7NOVDFHNrfZsubg6lId9czkEOy8qS02eErTpBztX0iss2bvffD87zB9+Mds2X1zS85ZTKm/bL4WysfrVBUL1mruipmvVqgZH8qCPQZbWeb0ok1CYHO4kSm1HnRdaehyuS4eI6XkYx/7GP/23/5bAPJjR6kKM59/dGVtvBZCCgXTEjLyudeoGWHLjp9Rm602xkz9OJJq2634BbVPonegRV04NCZYE73kY+1bUAxUYxTbrEqcS2TNFiZEBNvIv7bsnDIzBai1sVtOTQ1XaZHoRc34sCGEwOPxMDOzPOl2M8uc1vnhD39IMpUimZf88/e+x2233XbFMffffz+PPPLIxc9Pjo8wGUtxxx138I1vfINcLsfMzAzf/va3r/js1q1bGR8f59lnnwVgZmaGcrk8//9fCEyywq233spXawWrvvKVr/CqV72q4Wu0XDp+Rg0Qd22kO6POqPMT6kJBz+DOdprUNELdaylLhWqyPY46N5vFT4aqu72qxMsZ9d3A+uS/UqlUMZm0n2+I2WmSuPG3oXqgMFuhqOYFm0zaClDmZnwAhEIhbrtNLXP6ute9jte//vVLjjE6Osqv/uqvXhSnNFLmNJVKIaW8osxpnQMHDvDWt76V4fPneNdbXscNN9zA+fOXKnZf85rXcOzYMW655RYA3FbB5z77l+y78Xbe8Y53cP3119PV1XUxvDEXq9XKo48+yoc//GFyuRwOh4Mf/ehH3HXXXRe7yXzsYx+rHa1gElX+9E//hA984Nf5oz/6IyKRCF/84heXvDYrpp7WstQfwAS8APzzUsfecMMNspU89chvy8rHfTKTTsqn/uw9MvGJ/paeX2vGP7lRPvPf39aWcw+fOSrlJ7zymX/887acfyGe+6c/k/ITXnny5Wdac77/9gY59Hs7WnKuuRw9elTOziSkHH1ezqYTmp+vWMhLOfq8nImNaX6uRvniF78of/M3f1NKKWUmMSnl6PMyP5tZ9DP5XFbK0efV45tMJj4h5ejzspCfXfEYR48evWIbcFAu4FOXMxX5KHBMg2fFqrH17UARauaHKzPEpEU/8dRmkDRHcOQn2nLuuirREWy/KnEuA3vvA2DqcGvqfjiKMTLmFtf5qFHv1deKTi+lgrqQqIcaH/NhqVXSK+WvDI/MpVKT3Dejs8vlXJSRt7B3YkOOWggxALweaDyjvYWEN6g1P5LnXyJSHGbG1flCl7lkHb0ESu3p9DIbV+XrHh2oEufStXYbUyKEZbg1cWpXOUG+xfLxOuaaYEO2IJe6WlSLMZl1UuMD1LzkenqcxeagjAILCF/q1JWcpkXELivlooy8hWrRRmfUfwr8J2DBiihCiA8KIQ4KIQ5OT083w7aG6V2/g6I0I0cO0k2csn9DS8+vNSVXH5FqrGWLSXMp11SJgR6dPfyEYNS7l/XZQ1Qr2pec9FeTlB3tqcetmEyqc2pBA4F6xkczuqFogRCCorBjXqKSXt1RmzVw1K80uW1dXeolHbUQ4g3AlJTyucWOk1J+Xkq5X0q5PxJprczWZLYwYh5gfewJAGzdndvVZT6Efw1WUSY+1friTHJmnIK04PG39jttBLnuNiIkOXdy/r6ZzSKfy+IVs8gWdR+/HCklFcwoLXDUczM+9ErV4sQmi1ekBV56UIkypksk5c3CbLYgJSvuZSlXkK7XyP/iNuBNQogh4KvA3UKIv132mTQm4dpINzEA/GuujtS8OvbQGgDiY63v9GLJThBTgrqU4/ftuReAiZd+qOl5khfl46131Ha7nVgs9oo6UUNkvauL0v6uLothsrkRAoq5hePUSrVEWaOkNiEUKsK0ojccKSWxWAy7fXkNGZb8n0gpPwZ8TDVQ3An8Rynlu5dtocaUglsh/S8A9K7v3Ia28+HpGgQgM936BgKOwjRpc4j2V/m4kp71u4gSwDKsbceXdHScHsDibX0u+cDAACMjI4xMTWKuFjCltJvpViplTDMTFCw5bPG8ZudZLdVqBSU9RcGcw+aef4G3nByjKsxYU9rkP5ST01RFHGt8+XXC7XY7AwPLW/O5KvKoARz9O2AIJgnR7VpcstpphPs3AlCMXWj5ub2lKFG3TlWeQjDs3cu69AtUK1UUjfKpZ2txemcb5OMWi4X169fz1OP/m5svfI78QxPY7dpkZLz8xDe57sfv5fB9f8t1+1uj+FwpFz71DnK2NVz3n79/xT4pJdlP3sWR7jdy/W/8lSbnf/nh38RezrD1/3tGk/EvZ1l3tpTyJ1LK+YvRtpnIhj0ARG1r2muIBngCEXLSCqnWxqillASrcUqO9sRmG6G69la6iTN0+ohm56jLxz3h9r1XmPxqemRsXLuHdXZULaLUs3GPZudoFlO+XQzmjiDn6fiSTsZxixx4tUspzdvCeMtxzca/HP0FHldIz7ptZLGT9W5stylNRygK06YI1mxrHfVMOqHe8J72tuBajL7r63HqhYu/r5bKjCofD0Ta56gdYbXmS3LinGbnENPHSeAh1KWvnPl56d9PkDTDZ68MbdQLmFmC2k3aKs4IQZmc90GhBVeNo1bMZmJv/Trb3v777TZFE9KWLtyF1uZSJyZV2brZr19H3bPxehJ4US5ol08tstNkpR2706PZOZbC06WmR+Y0rPkSSB9nzDqoy4Xjywlfp9bVmDjysyv2zUwOAeCKaJdSKtzd2ESJdLI1s2r9fyPLYO2uV+Ft46xHS3KOXgLl1uanp6dUp+AI6kvsMhehKFzw7GXtzAuaNVcw56IkFb8mYzdKqG8QgFJiRJPxi4U8g6WzzAR3azJ+s1m7dR+z0kZl+Nkr9tULmAV6tSt1bPaptW+S062pwXNVOeqrmYqnn7BMUCgsnujfTHJx1Sl4u/Qd9y+vvZU+pjl/RpsVfnshxoy5ParEOm5vkIx0INJjmox/4fhBrKKMZe0NSx+sAxSzhSH7NoKJF6/YV02NUJGCUI92rePstbfMmZg238flGI66QzAFBlCEJDrWusyPSlK9CYN6UyVeRu9uNU49+qI2cWpXOUGuTfLxucRMYSyz2jQ6jp1UW5v1Xndl+VC9kgnvYUP5LLPZS8uQWjJjREVwwXrazcBdq0uei7em8bThqDsER3gQgOREC0UvmQmy2HF62lOMqFF6N+8lhRvl/C80Gd9XTVCyt7/DTdoSwV2Y0mRsMfY8CTz0ruscVa9j/c1YRIVzL1+aR+/ITZC0aJupFIiojrqcak2xNMNRdwi+nkEAZlsoerHMThJX2u+glkIoJs6797Am3fw4dblUxC9nqDrbL6HPO3o0W6cIpY4ybN/aEQuJddbsUhcUk6cuddT+0hRZu7b10z2BMEVpQmZas8DfOd/KNU64Ty00VU60roGAszDNjEX/jhqgvOZWBpjk/NCppo6bjE6gCIlog3z8ciruXkIyQanU3KptuewM6yrnyYY7YyGxjr97DeOiC9vEK2WIqpUq4WqUolvbpAKhmEgIP+ZcVNPz1DEcdYfgcHtJ4kaktVn1nw9fOUrO1n4H1Qhdu+4BYOyF5sapU1E1BmnVgaNW/P2YhCQ20dyH9fkjT2EWVRzrrux8onfGPTsZyB65+CYVi45hFyWEhmKXOmlzEFu+NZlYhqPuIOKmCPbZ1sTEZLVKqBqn7NJPr8TF6N+6nxmccP7nSx+8DLJxdUHV3gb5+OXYasW5khNDTR03efppAPp33NrUcVtBpW8/PUQZH1HXbhJjqiDIFtIu46POrCWIq2TkURtcxoy1G0+LRC/JRBS7KIFHX70SF0KYzAy597Im9VxT49SFpPpgdAfbn5/vjajOJxttbuaPaeIQUwSJ1HK1O4ngVjVLZfRlVfhSL1zm7tI+U6loD+OrGI7a4DIKrj7CVW1W/S8nPq7e8FZ/B8iJa5TW3s4aJhg6c7xpY5Zr8nF/pP3XIVQTcBTjzQ1/dWeOMurc1tQxW8Xa7TdRlGZK59XiSIXaQyyoodilTsXVRUCmWtLQw3DUHUTV24+PLDPphObnmqnd8I6wvsUuc+nb+1oARp+/sqLaislOUZRm3N72pyh6AhHy0gLp5tV8SSdjrK2Oku+6vmljthKLzcGQdRO++CF1Q3qEojS3pC6L4u7GLKrEo9rnUhuOuoMwB1SnGRvTrjBPnUKtV6JP56rEufRs2ksMP+YLV9Z/WCmm2Shx4ddF2ppQFKJKGEsT1ykuHFZrpLgHO28hsU4ytIcNxVMUCnks2XGmlTBCMWl+XotfDQump7Uvltb+u8+gYepxt5SGFdTqVFLqLCHY3TmOGiEY9u1nY+Y5yuXmvI7aCjFm2tR9fD5SlgiufPPWKWbOqiGDNTs7R5F4OdZ1N+EQRc4deRZXfoKUxmKXOs6AusCcbYGM3HDUHYS/R4275TWsoFZHyUyQwo3N4db8XE1lwx1ESHL66KItPhvGWYoza2m/fLxOztGNr9y83F3r5CFGRTf+cGcsGs9Hf034Ej/xC/ylKWYdrfm/eMJqsbJ8wgh9GMwh3DtIVQqqLRC9WHNTJBT9OKhGWXPD6wCYfumxpoznqyQo2vQj+im7egk3sSN9X/YYE67O7jEa6d9ElADmsWeIyDgVjcUudfy1ut2VtPYps4aj7iDMVhsxEcCU0f5Vy1WcJmMNa36eZhMa2MK46MYxsvq6H9VKFb9MUXHq5zoI3wBWUWlKR/r41Ci9TFPq2dsEy9qIEIy4d7I1rQp3hK81ZXmdbj+z0gZZ7TOxDEfdYcTNXThy2r9q+cox8vb2q/FWwnjoAJtzL1Iork5qnU5MYxUVcOvnOthrtcETE6uv+TJcW0j0bDiw6rHaTbFnHz6RBcAe1l7sAoAQJBQ/5lnt1YmGo+4wsvZufEVtRS/lcpmQTFBxdWbc0rLpLnwiy4kXVqdSTEbVN5d2dB9fCFdN9NKMjvSzQ89QlYJ1O29Z9Vjtxrf5FVWlt1bArBVkzEHsBe3rfRiOusMoufuIVKOa9mpLTI9hERWEt/1qvJUweKOaT506srq6H9larWG7Tz+OOtA7CEAxvvp1Csf0SwybBnSRI75a1u28lbJU3VmoVsCsFeSsIdwtaHJrOOpOwzeAQxSJR7VbwEhMqmIXa6AzHbUn1M950zo8E6vro5irrea7Qvq5DoFwH0Vpoppa3TqFrFYZyB1nyrO9SZa1F7vLy3nLemalDY+vdWsKRUcEX1V7AZrhqDsMa1B99Y1rKHrJRlWJsius316JSzEduZmthSNkstkVj1FOq4tEPh3Ix+soJhNRJYQlu7p1isnRc4RJUu3t8IXEOWQ2PcjZ4B0gRMvOWXV2EWSGQiGv6XkMR91heLoGAZiZHtLsHIWEmlHg727RoowGuLbejUMUOXnwX1Y8RjUzSUUKfAH9LCYCpMwRnKsUvYwdVbNi/Js6fyGxzvXv/Dg7P/r1lp7T5FXvjfi0tplYhqPuMIJ9tcI8Ta6gNpdquqZK7CD5+OWs338/FSnIHl+5ozbNRkkKH4rZ3ETLVs+svRtfaXWZBoXzz1GSJtbtuLlJVl2bWOtNbjWWkRuOusMIRPooSjNSwwYCSmaCOD5MFqtm59AauyfAWetWQlNPrXgMayFKyuRvnlFNouTqJbzKBWV37CXOmwexO1xNtOzaw1krf5uNGY7aYA5CMTGthLFoKHqx5aZJmvSjxlspqZ5b2FI+SSweW9HnHcUEWbP+1JnC14ddlEjGVya0kNUqawsniPuujoXEdlJfvyimtE2ZNRx1B5K0dOHKa5f14S5NM2NtfzPX1eLbcS9mUeXssyuTk3t0Jh+vYw2oi7yx8ZUtKI+cPYqPLPTta6ZZ1yT+iPpdaC0jNxx1B5Jz9OIvaSdbDVRiFB36WkBbCev33EVBWiicenzZn5VSEqgmKTn0Ix+vc1H0MrUy0cvkcbVrd2hL5wtd2o3V7mQGJ0JjGbnhqDuQsqePiIxTLpWaPnahkCcoU1TdnalKnIvZ7uKsYyc98aeX/dlsJoVTFMClvzeLQE15V4itbJ2iNPwceWlh3TZjRt0MEkoAa05bGbnhqDsQxT+AWVSZnmh+5kd8cgRFSBRf+5u5NoNs/21sqg4xPrY8JV9ySl0DMHv192YR7F5DRQqqqZUtYPniL3PeshGz1dZky65NMuYQjuLK1kEaxXDUHYg9pDYQSK4wRrkYySnV+dsD+hF5rIbw7vsAGDq4vPZcM7Vi8Da//h5YJrOlVkVx+aKXcqnEuuIpkoGdGlh2bZK3aS8jNxx1B+LrHgQgMzXU9LFno+oszd1BvRIXY+2O28jgRJ796bI+l0uoi0OOgD5DQElzBMcKRC/Dp17EJQqY1tyggVXXJiVHhIDGMnLDUXcgof6NAJQ1aCBQTHa+KnEuitnCOdce1iSfRUrZ8OeKadUJ+sL6fLPI2rvxrGBBefqEupDYtdVYSGwa7i48Ikc2k9bsFIaj7kDcviAzOBAaiF6q6QnKUsEf1t8r/0oprn0Va5jg/NkTDX+mOqM6an9En9eh6OwhXIkt6+EDUB19jox0MLBpt0aWXXuYPOpbV6IJzRwWwnDUHUpMiWBdZWGe+TBnJ4iJAMKkL9n0aujdez8Aoy80HqdWZqdJ4cJitWtl1urw9uMWOdKp5b1yB5JHOG/bjGLSvkv3tYKt1uR2JqqdCG1JRy2EWCOEeFwIcVQIcUQI8VHNrDFomLS1G0+h+Wooe36KlFl/Io/V0LtpL3F8mIeeaPgzllyUpKLfOs2W2mLvcqooFgo51pfOMhPapZVZ1yT1Mriz8TY6aqAM/Acp5XbgZuA3hRCG9rTN5J29hCrNT7L3lqLM2vSXO7wahKJwwbefDZnnqFQaq4/hKMbJmvXrqJ010Ut6GQvKF44dxCrKWNfu18iqaxN/TUZeSmvXIm9JRy2lHJdSPl/7eQY4BuhzheUaourtJ0ia3OzK6y3Ph6pK1E9Hk2Yh17+aCEnOHH2uoePd5QR5q/7qfNSpZ/7klyF6iZ1UC1T1bLt1iSMNloMv1EtVCqpp7ep9LCtGLYQYBPYCV0i9hBAfFEIcFEIcnJ7WvtnjtY45oKbPTY+ebdqY2WwGv8ggPfpMSVsNa25Q23NNvtRY3Q9/NUnJod83i1CPmktfSTbuqMXYCyTw0Ltui1ZmXZOYLFaSwoOiYZPbhh21EMIN/APwW1LKK/JQpJSfl1Lul1Luj0T0e4NfLTgj6i9qaqJ5opf4pJruZ/bpp/VUswiv2cq46MIx8oslj83nc3hFFunUX52POlabnRj+ZYleIukjjNi3IhQjh6DZpExBrHntmtw29I0JISyoTvorUsp/1Mwag4bxd6sNBGab2EAgVVclBq/OyNZY8ACbZw9RLC5eIyVR69ahePQdAoqbw9hzjVVtm82mWVu5QDZspOVpQdYSxKmhjLyRrA8B/B/gmJTyf2hmicGyCPUPAlBJNM9R52rxTk+kc3slLoZ50134RJaTh3626HH1NCubjrqPz0fW2oWn2Njr9vkjT2MWVezrbtTYqmuTgi2MV0MZeSMz6tuA9wB3CyEO1f48oJlFBg1hs7uI4cM007yUoFJSfY2uV2e72lh/4+sASBxZvD1XPc3KEdSn2KVOwdlDqNqYo06eUpeVBnYaC4laUHZGCMrEqrruLMaSqgYp5c+B1rX1NWiYuLkLe66JKUEz4xSkBbdPv7HZ1eAN93PetA7v+OJx6mJKTXt0B/Udq5eefnzRLNmZFC6Pb9FjzRMvME2QSO9ga4y71nB3q113UnH8geb//hirCh1MxtaNr9i8lCBzdoKYEryqF5umwzexpXCEbHbhtMZyTT4e7NK3o66LXmITQ0se2505yqhzm8YWXbuYfWqmVFIjGfnV+xt5DVB09RGpTDftdctZmCZ9lakSL8ex7W4cosjJ53684DEiO8WstGF3eVto2fJx1CocpicX7/SSSsZYK8fId+1pgVXXJvZaOdxM1HDUBpfj7ccl8qSTq1/ESM3M0FMcIufQd1x2tWy44bVUpCB7fOE4tTkXI6H4W2fUCvF1qymas9HFqyheeFkN9bjWG4pErfDUZOS5pDYycsNRdzCWkCojjo6dWfVYz/3jnxImReBV/2bVY+kZhzfAWesWglNPLXiMvRhjRofdxy8nVIs3LyV6mTn7DADrdt6utUnXLP4uNVOqnNKmya3hqDsYV030MjM5tKpxEskku8/+FSccexjcf/Un9CR7bmVz6SSJxPxvIq5SnLxFv3U+6tidHpK4ETOLLyjbpl5kVHTjDek73bCT8QQilKSJakabJreGo+5gQr0bAMjHVtaNus4L//jHhEUKx/0fB3H1J/j4tt+DRVQ48+wP5t9fTVK0d0bmS9wUxja7+CyuL3uMSbdRR01LhGIiIfyYNZKRG466gwl2r1Gf4smVL2BEYzH2nv8Sx1w3snbPPU20Tr+s33s3BWmhcOrxK/aVSyX8Mk3V2RllEDLWLtzFhWdx0clRepmm1L2ndUZdo6TNAWwaycgNR93BKGYzUSWIJbPyBYyX/+EzBMQM3td9snmG6RyL3cVZ+w66Y89csS8Rn8AkJMKjv+7j85F39BCsLOwcRg7/HADvxgOtMumaZdYSwlXSRkZuOOoOJ2nuwrlC0cvU1AQ3jP4Nhz230X+NLTRl+29jU/Uck+OXZkyka3U+rN7OiOdWPX2ESJHPzc67f3boIFUpWLvD6JGoNQV7GF9Fmya3hqPucGYdPfjLK1vAOPoPf4BXzBJ+w+812Sr9E9x1HwDnDl4ap87G1YeeXafdxy/H5FezDWLj869TOKMvMWwawOXV/+Jop9N3x/uYfdXvaDK24ag7nJK7n0g1SqVSWdbnxsaG2T/xKC/57qZn67VXqGdw1+1kcCDP/OSS7fmkujBXz4vVO3XRS3KezB9ZrTKQO860x1hIbAX9e+9n8J5f12Rsw1F3OMI3gFVUiC9TunrqHz+NgwI9b/6kNobpHMVs4ZxrD2uSz17SybuSVt9OvJHOcNSeyMKil4mRM4RJUu3d22qzDJqM4ag7HHtN9BIfa7zTy/CFcxyY/gcOh+6na8P1WpmmewprbmeACYbPnnhlY3aKojTj8XaGlD7UNwhAOXGl6GX86JMABDbf1EqTDDTAcNQdjqfWOy+zjCan577xX7FQZuAanU3X6dmjtucaeeGVOLVpdpqE8HVMYSq3N8AMDsQ85W7zFw5SkibW7jAcdafTGXejwYKE+1TRSzG+eL2HOkNnTnBT7Ju83PUGQuuu09I03dO/ZR8JvJjPP3Fxm7UQZ0bH3cfnI6aEsc4jevHEXuKCeRCb3dUGqwyaieGoOxxPIMKstCFSjTU5HfnWpxDA4Fs+qaldnYBQFIa8+1k/c5BqRa1A6CrFmbXov87HXGasXbgLl5a7rVaqrMufJObb0SarDJqJ4ag7HKEoRE1hLNmlRS9nTr7MTcnvcbjnQQJ9G1tgnf6R6+8gQpIzx54HwFtJULB1Rny6Tt7eg798qehl+OwRvCKL0r+vTVYZNBPDUV8FpCzdV8yo5mPy25+igsLGX/pEC6zqDNbsU9tzTb30A6qVKgGZotIh8vE6FU8vYZmgVCxc3DZ1XF1IDG65uV1mGTQRw1FfBeSdvQSXEL2cPPwcN6V/yJGBd+DrXtsiy/RPZN02xkUX9uFfkE7GsIoywtVZjtrk60MRktjkK+sU5eGD5KWFtVuNGfXVgOGorwIq7j5CMkmhkFvwmPh3P0VBWNn61v+vhZZ1BmOBA2yaPUR0QlX3mb2dUeejji1UE73MacnlSxzhvHUjZqutTVYZNBPDUV8FmAJrUIQkOnZh3v1HXniSm2d/wrG178Kt887a7cC86dX4RJaJ574NvNJWqVPwdqmil+y0+v2XSyXWFU+R9O9qp1kGTcRw1FcBjpo6LTE+v+hl9gf/lRmcbPul/9JKszqGwf1qnDoy9M8AuEKd5aiDvesBKCZUdeqFky/gEgXMa25op1kGTcRw1FcBvproJRe9sjDPy8/+hBvzv+Dk+vfi8ndGMfxW4+taw3nTWrZWT6v/Dve32aLl4fGHyUkrpFVHPX1CbTPWtdVYSLxaMBz1VUBd9FJOXBr6kFJS+uHvk8LNjrc+1A7TOobpsKreq0iBL9gZJU7rCEUhqoSxZFXRixx9ngwO+jftbrNlBs3CcNRXAQ63V+2dl760MNOLTz7GvuKznN7yAezuzlLbtRrblrsBSAovitncZmuWT9oawVVL0QwmD3PBthnFZGqzVQbNwnDUVwkxUxf2OTJiKSXK458mjo+dD/6HNlrWGWy88X4qUpA2deYDLWfvwV+aJp/PMVg+RzpozKavJgxHfZUwY+vGW3jFUb/wxLfYXXqRc9d9CJvT20bLOgOnN8Rpxy7Szs7MMS+7ewnLOOcOP41VlLGtNRYSryY67x3PYF6Kzl5Csy8BasF4288eZkqE2P3gb7XXsA5i44e/haJ0ZrhA8fVhGa0QP6SmGPZuv7XNFhk0E2NGfZVQ9Q7gI8tMOsFzP/46O8pHGdn5m1hsznab1jGYXQEUR2e+fdiCquilZ+xHJPHQvWZLmy0yaCaGo75KsNR+UadHzuB58jOMiy6uf9O/a7NVBq3CFVFDNhurQwzbt3ZMPW2DxjC+zasEV030Mv7Dv2Br5TQTez+KyWLIh68Vgj2DF3/Oho2FxKsNw1FfJQRq6rRb4t9kROnj+gf+bZstMmglgUgvRakuOTnXX3vNiq92DEd9lRDqWUdVCrWK2v7/gGK2tNskgxYiFBNRRa2j3b/9tjZbY9BsjKyPqwSz1cakEiKvONn92l9ttzkGbSBpiWAploj0rmu3KQZNxnDUVxHZN3wOV7AH0aEpZgarQ9z2USZm03RWNW2DRmjIUQshXgv8GWACviClfFhTqwxWxIYb7m23CQZt5LpXv73dJhhoxJIxaiGECfhfwOuA7cAvCyG2a22YgYGBgYFKI4uJB4DTUsqzUsoi8FXgzdqaZWBgYGBQpxFH3Q8Mz/n3SG2bgYGBgUELaFp6nhDig0KIg0KIg9PT080a1sDAwOCapxFHPQqsmfPvgdq2S5BSfl5KuV9KuT8SMdadDQwMDJpFI476WWCzEGK9EMIKvBP4lrZmGRgYGBjUWTI9T0pZFkL8O+AHqOl5j0gpj2humYGBgYEB0GAetZTyu8B3NbbFwMDAwGAehJSy+YMKMQ1c2RK7McJAtInmNBvDvtVh2Lc6DPtWh57tWyelnHeBTxNHvRqEEAellPvbbcdCGPatDsO+1WHYtzr0bt9CGNXzDAwMDHSO4agNDAwMdI4eHfXn223AEhj2rQ7DvtVh2Lc69G7fvOguRm1gYGBgcCl6nFEbGBgYGMzBcNQGBgYGOqdtjloI8VohxAkhxGkhxEPz7LcJIR6t7X9aCDHYQtvWCCEeF0IcFUIcEUJ8dJ5j7hRCpIQQh2p/Pt4q+2rnHxJCvFw798F59gshxJ/Xrt9LQoh9LbRt65zrckgIkRZC/NZlx7T0+gkhHhFCTAkhDs/ZFhRC/FAIcar2d2CBz76vdswpIcT7WmjfHwkhjte+v38SQvgX+Oyi94KG9n1SCDE65zt8YIHPLvq7rqF9j86xbUgIcWiBz2p+/VaNlLLlf1Cl6GeADYAVeBHYftkxvwF8tvbzO4FHW2hfL7Cv9rMHODmPfXcC/9yO61c7/xAQXmT/A8D3AAHcDDzdxu96AjWZv23XD7gD2AccnrPtvwEP1X5+CPjMPJ8LAmdrfwdqPwdaZN9rAHPt58/MZ18j94KG9n0S+I8NfP+L/q5rZd9l+/878PF2Xb/V/mnXjLqRZgRvBv669vPXgXuEEKIVxkkpx6WUz9d+ngGO0Xk1uN8MfFmqPAX4hRC9bbDjHuCMlHKlStWmIKV8AohftnnuPfbXwIPzfPR+4IdSyriUMgH8EHhtK+yTUj4mpSzX/vkUauXKtrDA9WuEljQeWcy+mt94O/B3zT5vq2iXo26kGcHFY2o3awoItcS6OdRCLnuBp+fZfYsQ4kUhxPeEEDtaaxkSeEwI8ZwQ4oPz7NdLw4d3svAvSDuvH0C3lHK89vME0D3PMXq5jr+G+oY0H0vdC1ry72qhmUcWCB3p4fq9CpiUUp5aYH87r19DGIuJiyCEcAP/APyWlDJ92e7nUV/nrwf+AvhGi827XUq5D7WX5W8KIe5o8fmXpFYW903A38+zu93X7xKk+g6sy1xVIcR/AcrAVxY4pF33wv8GNgJ7gHHU8IIe+WUWn03r/nepXY66kWYEF48RQpgBHxBriXXqOS2oTvorUsp/vHy/lDItpczUfv4uYBFChFtln5RytPb3FPBPqK+Yc2mo4YPGvA54Xko5efmOdl+/GpP1cFDt76l5jmnrdRRCvB94A/Cu2sPkChq4FzRBSjkppaxIKavAXy1w3nZfPzPwS8CjCx3Truu3HNrlqBtpRvAtoL7C/jbgxwvdqM2mFtP6P8AxKeX/WOCYnnrMXAhxAPVatuRBIoRwCSE89Z9RF50OX3bYt4D31rI/bgZSc17zW8WCM5l2Xr85zL3H3gd8c55jfgC8RggRqL3av6a2TXOEEK8F/hPwJinl7ALHNHIvaGXf3DWPtyxw3nY3HrkXOC6lHJlvZzuv37Jo1yomalbCSdQV4f9S2/Yp1JsSwI76ynwaeAbY0ELbbkd9DX4JOFT78wDwIeBDtWP+HXAEdRX7KeDWFtq3oXbeF2s21K/fXPsE8L9q1/dlYH+Lv18XquP1zdnWtuuH+sAYB0qocdJ/g7rm8S/AKeBHQLB27H7gC3M++2u1+/A08KsttO80any3fg/Ws6D6gO8udi+0yL6/qd1bL6E6397L7av9+4rf9VbYV9v+pfo9N+fYll+/1f4xJOQGBgYGOsdYTDQwMDDQOYajNjAwMNA5hqM2MDAw0DmGozYwMDDQOYajNjAwMNA5hqM2MDAw0DmGozYwMDDQOf8/g0ycihLbLE4AAAAASUVORK5CYII=", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] @@ -450,15 +970,41 @@ "plt.plot(y_test[0:20])\n", "plt.plot(predictions[0:20])\n", "plt.legend([\"this is test\", \"this is prediction\"])\n", - "plt.show()\n", - "\n", - "\n" + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4993447.52575" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df[\"price\"].mean()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Since we have nearly perfect prediction we don't need to proceed with polynomial Regression. Our data has a complete linear relation. Our rmse is 3416 while the mean price per house is 4.993.447.\n", + "So to visualize our accuracy again. If we subtract the 3416 from the mean value and divide the result by our mean value we get our accuracy as result." ] } ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3", "language": "python", "name": "python3" }, @@ -472,7 +1018,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.2" + "version": "3.9.7" } }, "nbformat": 4,