{ "cells": [ { "metadata": {}, "cell_type": "markdown", "source": "", "id": "8a77807f92f26ee" }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T10:00:23.434531Z", "start_time": "2026-04-25T10:00:23.381273Z" } }, "cell_type": "markdown", "source": [ "## This is the Q1 Notebook!\n", "\n", "It's tracked via GitHub! hence the need for this line for the init commit" ], "id": "193cc36275a60171" }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.185419800Z", "start_time": "2026-04-25T18:32:46.161551700Z" } }, "cell_type": "code", "source": [ "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns" ], "id": "edaea0c939a83b79", "outputs": [], "execution_count": 868 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.231687200Z", "start_time": "2026-04-25T18:32:46.204273900Z" } }, "cell_type": "code", "source": "df = pd.read_csv('data/googleplaystore_new.csv')", "id": "e657e9baacc13e6b", "outputs": [], "execution_count": 869 }, { "metadata": {}, "cell_type": "markdown", "source": "## Part A\n", "id": "751a6161e8e12bdd" }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.287290300Z", "start_time": "2026-04-25T18:32:46.263732800Z" } }, "cell_type": "code", "source": [ "df = df.dropna()\n", "df = df.drop_duplicates()" ], "id": "756c92821453bbb3", "outputs": [], "execution_count": 870 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.328054400Z", "start_time": "2026-04-25T18:32:46.288288200Z" } }, "cell_type": "code", "source": "df.head(10)", "id": "4e1be303d63f47a4", "outputs": [ { "data": { "text/plain": [ " App Category Rating Reviews Size \\\n", "0 Market Update Helper LIBRARIES_AND_DEMO 4.1 20145 11k \n", "1 SuperLivePro BUSINESS 4.3 46353 21M \n", "2 Wifi Connect Library LIBRARIES_AND_DEMO 3.9 58055 41k \n", "3 Apk Installer LIBRARIES_AND_DEMO 3.8 7750 292k \n", "4 English speaking texts EDUCATION 4.4 1619 3.0M \n", "5 Eternal life LIBRARIES_AND_DEMO 5.0 26 2.5M \n", "6 Dresses Ideas & Fashions +3000 BEAUTY 4.5 473 8.2M \n", "7 GO Notifier COMMUNICATION 4.2 124346 695k \n", "8 Prosperity EVENTS 5.0 16 2.3M \n", "9 NSE Mobile Trading FINANCE 4.1 13868 1.4M \n", "\n", " Installs Type Price Content Rating Genres Android Ver \n", "0 1,000,000+ Free 0 Everyone Libraries & Demo 1.5 and up \n", "1 1,000,000+ Free 0 Everyone Business 1.5 and up \n", "2 5,000,000+ Free 0 Everyone Libraries & Demo 1.5 and up \n", "3 1,000,000+ Free 0 Everyone Libraries & Demo 1.6 and up \n", "4 1,000,000+ Free 0 Everyone Education 1.6 and up \n", "5 1,000+ Free 0 Everyone Libraries & Demo 1.6 and up \n", "6 100,000+ Free 0 Mature 17+ Beauty 1.6 and up \n", "7 10,000,000+ Free 0 Everyone Communication 2.0 and up \n", "8 100+ Free 0 Everyone Events 2.0 and up \n", "9 1,000,000+ Free 0 Everyone Finance 2.1 and up " ], "text/html": [ "
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2Wifi Connect LibraryLIBRARIES_AND_DEMO3.95805541k5,000,000+Free0EveryoneLibraries & Demo1.5 and up
3Apk InstallerLIBRARIES_AND_DEMO3.87750292k1,000,000+Free0EveryoneLibraries & Demo1.6 and up
4English speaking textsEDUCATION4.416193.0M1,000,000+Free0EveryoneEducation1.6 and up
5Eternal lifeLIBRARIES_AND_DEMO5.0262.5M1,000+Free0EveryoneLibraries & Demo1.6 and up
6Dresses Ideas & Fashions +3000BEAUTY4.54738.2M100,000+Free0Mature 17+Beauty1.6 and up
7GO NotifierCOMMUNICATION4.2124346695k10,000,000+Free0EveryoneCommunication2.0 and up
8ProsperityEVENTS5.0162.3M100+Free0EveryoneEvents2.0 and up
9NSE Mobile TradingFINANCE4.1138681.4M1,000,000+Free0EveryoneFinance2.1 and up
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" ] }, "execution_count": 871, "metadata": {}, "output_type": "execute_result" } ], "execution_count": 871 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T13:14:34.819448Z", "start_time": "2026-04-25T13:14:34.807334900Z" } }, "cell_type": "markdown", "source": "## Part B", "id": "5e0e0e76635904b6" }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.394614Z", "start_time": "2026-04-25T18:32:46.330567300Z" } }, "cell_type": "code", "source": [ "# Getting the column for size, checking if it's ending with an M or a k and converting the Mb to kb with 1024* and then again from kb to just b by another 1024*\n", "def parse_size(size_str):\n", " if isinstance(size_str, str):\n", " if size_str.endswith('M'):\n", " return float(size_str[:-1]) * 1024 * 1024\n", " elif size_str.endswith('k'):\n", " return float(size_str[:-1]) * 1024\n", " return size_str" ], "id": "c15cb7f9831e0f81", "outputs": [], "execution_count": 872 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.448348600Z", "start_time": "2026-04-25T18:32:46.396618500Z" } }, "cell_type": "code", "source": "df['Size in bytes'] = df['Size'].apply(parse_size)", "id": "c76da70de24ddc72", "outputs": [], "execution_count": 873 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.538411700Z", "start_time": "2026-04-25T18:32:46.451372100Z" } }, "cell_type": "code", "source": "df[['Size', 'Size in bytes']].head(10)", "id": "73784ad66975e81f", "outputs": [ { "data": { "text/plain": [ " Size Size in bytes\n", "0 11k 11264.0\n", "1 21M 22020096.0\n", "2 41k 41984.0\n", "3 292k 299008.0\n", "4 3.0M 3145728.0\n", "5 2.5M 2621440.0\n", "6 8.2M 8598323.2\n", "7 695k 711680.0\n", "8 2.3M 2411724.8\n", "9 1.4M 1468006.4" ], "text/html": [ "
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" ] }, "execution_count": 874, "metadata": {}, "output_type": "execute_result" } ], "execution_count": 874 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.627364Z", "start_time": "2026-04-25T18:32:46.563472Z" } }, "cell_type": "code", "source": "print(11*1024) # Just checking the kb and mb conversion happened properly, by checking 2 of the values manually.", "id": "7ac34d8bc88327a1", "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "11264\n" ] } ], "execution_count": 875 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.670395800Z", "start_time": "2026-04-25T18:32:46.628364600Z" } }, "cell_type": "code", "source": "print((21*1024)*1024) # Ideally this is the same as doing the calculation without the ( ) but just incase!", "id": "f72b05042c5a16fa", "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "22020096\n" ] } ], "execution_count": 876 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.696603800Z", "start_time": "2026-04-25T18:32:46.671400500Z" } }, "cell_type": "code", "source": "print(1.4*1024*1024) # This one seemed odd... Checked on an online converted to double-check but turns out the 0.4 bytes shows up there too.", "id": "dcaf54123ea0d75d", "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1468006.4\n" ] } ], "execution_count": 877 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.720540800Z", "start_time": "2026-04-25T18:32:46.700613100Z" } }, "cell_type": "code", "source": "df.head(10)", "id": "3e1112ae100d010c", "outputs": [ { "data": { "text/plain": [ " App Category Rating Reviews Size \\\n", "0 Market Update Helper LIBRARIES_AND_DEMO 4.1 20145 11k \n", "1 SuperLivePro BUSINESS 4.3 46353 21M \n", "2 Wifi Connect Library LIBRARIES_AND_DEMO 3.9 58055 41k \n", "3 Apk Installer LIBRARIES_AND_DEMO 3.8 7750 292k \n", "4 English speaking texts EDUCATION 4.4 1619 3.0M \n", "5 Eternal life LIBRARIES_AND_DEMO 5.0 26 2.5M \n", "6 Dresses Ideas & Fashions +3000 BEAUTY 4.5 473 8.2M \n", "7 GO Notifier COMMUNICATION 4.2 124346 695k \n", "8 Prosperity EVENTS 5.0 16 2.3M \n", "9 NSE Mobile Trading FINANCE 4.1 13868 1.4M \n", "\n", " Installs Type Price Content Rating Genres Android Ver \\\n", "0 1,000,000+ Free 0 Everyone Libraries & Demo 1.5 and up \n", "1 1,000,000+ Free 0 Everyone Business 1.5 and up \n", "2 5,000,000+ Free 0 Everyone Libraries & Demo 1.5 and up \n", "3 1,000,000+ Free 0 Everyone Libraries & Demo 1.6 and up \n", "4 1,000,000+ Free 0 Everyone Education 1.6 and up \n", "5 1,000+ Free 0 Everyone Libraries & Demo 1.6 and up \n", "6 100,000+ Free 0 Mature 17+ Beauty 1.6 and up \n", "7 10,000,000+ Free 0 Everyone Communication 2.0 and up \n", "8 100+ Free 0 Everyone Events 2.0 and up \n", "9 1,000,000+ Free 0 Everyone Finance 2.1 and up \n", "\n", " Size in bytes \n", "0 11264.0 \n", "1 22020096.0 \n", "2 41984.0 \n", "3 299008.0 \n", "4 3145728.0 \n", "5 2621440.0 \n", "6 8598323.2 \n", "7 711680.0 \n", "8 2411724.8 \n", "9 1468006.4 " ], "text/html": [ "
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1SuperLiveProBUSINESS4.34635321M1,000,000+Free0EveryoneBusiness1.5 and up22020096.0
2Wifi Connect LibraryLIBRARIES_AND_DEMO3.95805541k5,000,000+Free0EveryoneLibraries & Demo1.5 and up41984.0
3Apk InstallerLIBRARIES_AND_DEMO3.87750292k1,000,000+Free0EveryoneLibraries & Demo1.6 and up299008.0
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8ProsperityEVENTS5.0162.3M100+Free0EveryoneEvents2.0 and up2411724.8
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" ] }, "execution_count": 878, "metadata": {}, "output_type": "execute_result" } ], "execution_count": 878 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T13:28:40.682532800Z", "start_time": "2026-04-25T13:28:40.678521Z" } }, "cell_type": "markdown", "source": "# Part C", "id": "9883e69704d0a69e" }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.749478600Z", "start_time": "2026-04-25T18:32:46.738353Z" } }, "cell_type": "code", "source": "df['Numeric Installs'] = df['Installs'].str.replace('+', '').str.replace(',', '').astype(int)", "id": "c8d4f46526918c20", "outputs": [], "execution_count": 879 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.762648Z", "start_time": "2026-04-25T18:32:46.751624500Z" } }, "cell_type": "code", "source": "df.head(10)", "id": "cffd24a82d242352", "outputs": [ { "data": { "text/plain": [ " App Category Rating Reviews Size \\\n", "0 Market Update Helper LIBRARIES_AND_DEMO 4.1 20145 11k \n", "1 SuperLivePro BUSINESS 4.3 46353 21M \n", "2 Wifi Connect Library LIBRARIES_AND_DEMO 3.9 58055 41k \n", "3 Apk Installer LIBRARIES_AND_DEMO 3.8 7750 292k \n", "4 English speaking texts EDUCATION 4.4 1619 3.0M \n", "5 Eternal life LIBRARIES_AND_DEMO 5.0 26 2.5M \n", "6 Dresses Ideas & Fashions +3000 BEAUTY 4.5 473 8.2M \n", "7 GO Notifier COMMUNICATION 4.2 124346 695k \n", "8 Prosperity EVENTS 5.0 16 2.3M \n", "9 NSE Mobile Trading FINANCE 4.1 13868 1.4M \n", "\n", " Installs Type Price Content Rating Genres Android Ver \\\n", "0 1,000,000+ Free 0 Everyone Libraries & Demo 1.5 and up \n", "1 1,000,000+ Free 0 Everyone Business 1.5 and up \n", "2 5,000,000+ Free 0 Everyone Libraries & Demo 1.5 and up \n", "3 1,000,000+ Free 0 Everyone Libraries & Demo 1.6 and up \n", "4 1,000,000+ Free 0 Everyone Education 1.6 and up \n", "5 1,000+ Free 0 Everyone Libraries & Demo 1.6 and up \n", "6 100,000+ Free 0 Mature 17+ Beauty 1.6 and up \n", "7 10,000,000+ Free 0 Everyone Communication 2.0 and up \n", "8 100+ Free 0 Everyone Events 2.0 and up \n", "9 1,000,000+ Free 0 Everyone Finance 2.1 and up \n", "\n", " Size in bytes Numeric Installs \n", "0 11264.0 1000000 \n", "1 22020096.0 1000000 \n", "2 41984.0 5000000 \n", "3 299008.0 1000000 \n", "4 3145728.0 1000000 \n", "5 2621440.0 1000 \n", "6 8598323.2 100000 \n", "7 711680.0 10000000 \n", "8 2411724.8 100 \n", "9 1468006.4 1000000 " ], "text/html": [ "
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8ProsperityEVENTS5.0162.3M100+Free0EveryoneEvents2.0 and up2411724.8100
9NSE Mobile TradingFINANCE4.1138681.4M1,000,000+Free0EveryoneFinance2.1 and up1468006.41000000
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" ] }, "execution_count": 880, "metadata": {}, "output_type": "execute_result" } ], "execution_count": 880 }, { "metadata": {}, "cell_type": "markdown", "source": "## Part D", "id": "1818d3183dae5398" }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.785103900Z", "start_time": "2026-04-25T18:32:46.763648900Z" } }, "cell_type": "code", "source": "df.to_csv('data/googleplaystore_new_new.csv', index=False)", "id": "5a99edb9f8b29b12", "outputs": [], "execution_count": 881 }, { "metadata": {}, "cell_type": "markdown", "source": "# Part E", "id": "5372c799c0b2662" }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.792121900Z", "start_time": "2026-04-25T18:32:46.786105500Z" } }, "cell_type": "code", "source": [ "from sklearn.model_selection import train_test_split\n", "from sklearn.linear_model import LinearRegression, Ridge, Lasso\n", "from sklearn.preprocessing import PolynomialFeatures\n", "from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score" ], "id": "8cc741d5b19eaa62", "outputs": [], "execution_count": 882 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.803603800Z", "start_time": "2026-04-25T18:32:46.793716400Z" } }, "cell_type": "code", "source": "df_new = pd.read_csv('data/googleplaystore_new_new.csv')", "id": "bc158bb312aa3cd7", "outputs": [], "execution_count": 883 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.810420900Z", "start_time": "2026-04-25T18:32:46.803603800Z" } }, "cell_type": "code", "source": [ "columns_to_keep = ['Category', 'Reviews', 'Content Rating', 'Size in bytes', 'Numeric Installs', 'Rating']\n", "df_min = df_new[columns_to_keep]" ], "id": "585677f9cc3efc16", "outputs": [], "execution_count": 884 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.822566300Z", "start_time": "2026-04-25T18:32:46.810925Z" } }, "cell_type": "code", "source": "df_min.head(20)", "id": "76760facf2a6e8cb", "outputs": [ { "data": { "text/plain": [ " Category Reviews Content Rating Size in bytes \\\n", "0 LIBRARIES_AND_DEMO 20145 Everyone 11264.0 \n", "1 BUSINESS 46353 Everyone 22020096.0 \n", "2 LIBRARIES_AND_DEMO 58055 Everyone 41984.0 \n", "3 LIBRARIES_AND_DEMO 7750 Everyone 299008.0 \n", "4 EDUCATION 1619 Everyone 3145728.0 \n", "5 LIBRARIES_AND_DEMO 26 Everyone 2621440.0 \n", "6 BEAUTY 473 Mature 17+ 8598323.2 \n", "7 COMMUNICATION 124346 Everyone 711680.0 \n", "8 EVENTS 16 Everyone 2411724.8 \n", "9 FINANCE 13868 Everyone 1468006.4 \n", "10 COMMUNICATION 32254 Everyone 5767168.0 \n", "11 COMMUNICATION 125232 Everyone 2831155.2 \n", "12 EDUCATION 430 Everyone 538624.0 \n", "13 EDUCATION 275 Everyone 2411724.8 \n", "14 BOOKS_AND_REFERENCE 1778 Mature 17+ 5138022.4 \n", "15 BUSINESS 2287 Everyone 1572864.0 \n", "16 LIBRARIES_AND_DEMO 126862 Everyone 638976.0 \n", "17 COMMUNICATION 255 Everyone 1677721.6 \n", "18 LIFESTYLE 360 Everyone 4823449.6 \n", "19 EDUCATION 656 Everyone 569344.0 \n", "\n", " Numeric Installs Rating \n", "0 1000000 4.1 \n", "1 1000000 4.3 \n", "2 5000000 3.9 \n", "3 1000000 3.8 \n", "4 1000000 4.4 \n", "5 1000 5.0 \n", "6 100000 4.5 \n", "7 10000000 4.2 \n", "8 100 5.0 \n", "9 1000000 4.1 \n", "10 1000000 4.4 \n", "11 10000000 4.2 \n", "12 10000 4.0 \n", "13 50000 4.0 \n", "14 500000 3.9 \n", "15 1000000 4.4 \n", "16 10000000 3.5 \n", "17 10000 4.1 \n", "18 10000 4.1 \n", "19 10000 4.3 " ], "text/html": [ "
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CategoryReviewsContent RatingSize in bytesNumeric InstallsRating
0LIBRARIES_AND_DEMO20145Everyone11264.010000004.1
1BUSINESS46353Everyone22020096.010000004.3
2LIBRARIES_AND_DEMO58055Everyone41984.050000003.9
3LIBRARIES_AND_DEMO7750Everyone299008.010000003.8
4EDUCATION1619Everyone3145728.010000004.4
5LIBRARIES_AND_DEMO26Everyone2621440.010005.0
6BEAUTY473Mature 17+8598323.21000004.5
7COMMUNICATION124346Everyone711680.0100000004.2
8EVENTS16Everyone2411724.81005.0
9FINANCE13868Everyone1468006.410000004.1
10COMMUNICATION32254Everyone5767168.010000004.4
11COMMUNICATION125232Everyone2831155.2100000004.2
12EDUCATION430Everyone538624.0100004.0
13EDUCATION275Everyone2411724.8500004.0
14BOOKS_AND_REFERENCE1778Mature 17+5138022.45000003.9
15BUSINESS2287Everyone1572864.010000004.4
16LIBRARIES_AND_DEMO126862Everyone638976.0100000003.5
17COMMUNICATION255Everyone1677721.6100004.1
18LIFESTYLE360Everyone4823449.6100004.1
19EDUCATION656Everyone569344.0100004.3
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" ] }, "execution_count": 885, "metadata": {}, "output_type": "execute_result" } ], "execution_count": 885 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.852368200Z", "start_time": "2026-04-25T18:32:46.823731300Z" } }, "cell_type": "code", "source": "df_encoded = pd.get_dummies(df_min, columns=['Category', 'Content Rating'])", "id": "8c4742ab98b8b6ca", "outputs": [], "execution_count": 886 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.860385300Z", "start_time": "2026-04-25T18:32:46.853369300Z" } }, "cell_type": "code", "source": [ "X = df_encoded.drop('Rating', axis=1)\n", "y = df_encoded['Rating']" ], "id": "7faed3f843076351", "outputs": [], "execution_count": 887 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.878750100Z", "start_time": "2026-04-25T18:32:46.860889300Z" } }, "cell_type": "code", "source": "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=101)", "id": "8646df724923b0f5", "outputs": [], "execution_count": 888 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.884189Z", "start_time": "2026-04-25T18:32:46.879749500Z" } }, "cell_type": "code", "source": [ "def evaluate_model(model, X_train, X_test, y_train, y_test, name):\n", " model.fit(X_train, y_train)\n", " y_pred = model.predict(X_test)\n", "\n", " results = {\n", " 'Model': name,\n", " 'MAE': mean_absolute_error(y_test, y_pred),\n", " 'RMSE': np.sqrt(mean_squared_error(y_test, y_pred)),\n", " 'R2': r2_score(y_test, y_pred)\n", " }\n", " return results, y_pred" ], "id": "44c698b18cdce613", "outputs": [], "execution_count": 889 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.892720900Z", "start_time": "2026-04-25T18:32:46.885190900Z" } }, "cell_type": "code", "source": "results = []", "id": "d8740e0256fe177b", "outputs": [], "execution_count": 890 }, { "metadata": {}, "cell_type": "markdown", "source": "## Trying Linear Regression", "id": "e52a65f09530a141" }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.906083Z", "start_time": "2026-04-25T18:32:46.892720900Z" } }, "cell_type": "code", "source": [ "lin_model = LinearRegression()\n", "lin_res, y_pred_lin = evaluate_model(lin_model, X_train, X_test, y_train, y_test, \"Linear Regression\")\n", "results.append(lin_res)" ], "id": "db88942671bdf26a", "outputs": [], "execution_count": 891 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.917527900Z", "start_time": "2026-04-25T18:32:46.906083Z" } }, "cell_type": "code", "source": "X_test", "id": "32a5d474cc8ed681", "outputs": [ { "data": { "text/plain": [ " Reviews Size in bytes Numeric Installs Category_ART_AND_DESIGN \\\n", "303 70782 52428800.0 1000000 False \n", "805 132014 26214400.0 10000000 False \n", "352 58 15728640.0 10000 False \n", "952 1658 10171187.2 100000 False \n", "514 10852 18874368.0 1000000 False \n", "... ... ... ... ... \n", "1096 120 10485760.0 500 False \n", "551 27396 61865984.0 1000000 False \n", "660 11506 15728640.0 100000 False \n", "655 1015 11534336.0 100000 True \n", "473 7976 46137344.0 500000 False \n", "\n", " Category_AUTO_AND_VEHICLES Category_BEAUTY \\\n", "303 False False \n", "805 False False \n", "352 False False \n", "952 False False \n", "514 False False \n", "... ... ... \n", "1096 False False \n", "551 False False \n", "660 False False \n", "655 False False \n", "473 False False \n", "\n", " Category_BOOKS_AND_REFERENCE Category_BUSINESS Category_COMICS \\\n", "303 False False False \n", "805 False False False \n", "352 False False False \n", "952 False False False \n", "514 False False False \n", "... ... ... ... \n", "1096 False False False \n", "551 False False False \n", "660 False False False \n", "655 False False False \n", "473 False False False \n", "\n", " Category_COMMUNICATION ... 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333 rows × 26 columns

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" ] }, "execution_count": 892, "metadata": {}, "output_type": "execute_result" } ], "execution_count": 892 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:46.991337600Z", "start_time": "2026-04-25T18:32:46.918530100Z" } }, "cell_type": "code", "source": [ "residual_linear = y_test - y_pred_lin\n", "\n", "plt.figure(figsize=(8, 5))\n", "plt.scatter(y_pred_lin, residual_linear, alpha=0.5)\n", "plt.axhline(y=0, color='r', linestyle='--')\n", "plt.title(\"Part E - Linear Regression: Residual Plot\")\n", "plt.xlabel(\"Predicted Rating\")\n", "plt.ylabel(\"Residual (y - y_hat)\")\n", "plt.tight_layout()\n", "plt.show()" ], "id": "8c3be82a8033d876", "outputs": [ { "data": { "text/plain": [ "
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" }, "metadata": {}, "output_type": "display_data", "jetTransient": { "display_id": null } } ], "execution_count": 893 }, { "metadata": {}, "cell_type": "markdown", "source": "## Trying Polynomial Regression", "id": "28a6926de3a1a2e7" }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:47.011369400Z", "start_time": "2026-04-25T18:32:46.992338400Z" } }, "cell_type": "code", "source": [ "poly_converter = PolynomialFeatures(degree=2, include_bias=False)\n", "X_train_p = poly_converter.fit_transform(X_train)\n", "X_test_p = poly_converter.transform(X_test)" ], "id": "b867289f4b8dd0ae", "outputs": [], "execution_count": 894 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:47.042987600Z", "start_time": "2026-04-25T18:32:47.012369900Z" } }, "cell_type": "code", "source": [ "poly_model = LinearRegression()\n", "poly_res, y_pred_poly = evaluate_model(poly_model, X_train_p, X_test_p, y_train, y_test, \"Polynomial Regression\")\n", "results.append(poly_res)" ], "id": "61b135564e36f71d", "outputs": [], "execution_count": 895 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:47.112590600Z", "start_time": "2026-04-25T18:32:47.042987600Z" } }, "cell_type": "code", "source": [ "plt.figure(figsize=(6, 6))\n", "plt.scatter(y_test, y_pred_poly, alpha=0.5)\n", "plt.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], 'r--')\n", "plt.title(\"Part E - Polynomial Regression: Actual vs Predicted\")\n", "plt.xlabel(\"True Rating\")\n", "plt.ylabel(\"Predicted Rating\")\n", "plt.tight_layout()\n", "plt.show()" ], "id": "5358eeb45dc985", "outputs": [ { "data": { "text/plain": [ "
" ], "image/png": 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" }, "metadata": {}, "output_type": "display_data", "jetTransient": { "display_id": null } } ], "execution_count": 896 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T16:34:36.630819600Z", "start_time": "2026-04-25T16:34:36.611164400Z" } }, "cell_type": "markdown", "source": "## Trying Ridge Regression", "id": "46d1bd68d47ea764" }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:47.138233300Z", "start_time": "2026-04-25T18:32:47.128611600Z" } }, "cell_type": "code", "source": [ "ridge_model = Ridge(alpha=1.0, solver='lsqr')\n", "ridge_res, y_pred_ridge = evaluate_model(ridge_model, X_train, X_test, y_train, y_test, \"Ridge Regression\")\n", "results.append(ridge_res)" ], "id": "f7b09be17154ad47", "outputs": [], "execution_count": 897 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:47.210718200Z", "start_time": "2026-04-25T18:32:47.139738100Z" } }, "cell_type": "code", "source": [ "plt.figure(figsize=(6, 6))\n", "plt.scatter(y_test, y_pred_ridge, alpha=0.5)\n", "plt.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], 'r--')\n", "plt.title(\"Part E - Ridge Regression: Actual vs Predicted\")\n", "plt.xlabel(\"True Rating\")\n", "plt.ylabel(\"Predicted Rating\")\n", "plt.tight_layout()\n", "plt.show()" ], "id": "751e4cca3fc3b4bb", "outputs": [ { "data": { "text/plain": [ "
" ], "image/png": 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" }, "metadata": {}, "output_type": "display_data", "jetTransient": { "display_id": null } } ], "execution_count": 898 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T16:42:13.392229200Z", "start_time": "2026-04-25T16:42:13.355459900Z" } }, "cell_type": "markdown", "source": "## Trying Lasso Regression", "id": "fd2c011a69ca364f" }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:47.231714300Z", "start_time": "2026-04-25T18:32:47.211723200Z" } }, "cell_type": "code", "source": [ "lasso_model = Lasso(alpha=0.001, max_iter=10000)\n", "lasso_res, y_pred_lasso = evaluate_model(lasso_model, X_train, X_test, y_train, y_test, \"Lasso Regression\")\n", "results.append(lasso_res)" ], "id": "11024fb6674354a3", "outputs": [], "execution_count": 899 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:47.300748Z", "start_time": "2026-04-25T18:32:47.232718700Z" } }, "cell_type": "code", "source": [ "plt.figure(figsize=(6, 6))\n", "plt.scatter(y_test, y_pred_lasso, alpha=0.5)\n", "plt.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], 'r--')\n", "plt.title(\"Part E - Lasso Regression: Actual vs Predicted\")\n", "plt.xlabel(\"True Rating\")\n", "plt.ylabel(\"Predicted Rating\")\n", "plt.tight_layout()\n", "plt.show()" ], "id": "3f0658c719c2ecc6", "outputs": [ { "data": { "text/plain": [ "
" ], "image/png": 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" }, "metadata": {}, "output_type": "display_data", "jetTransient": { "display_id": null } } ], "execution_count": 900 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:47.322487800Z", "start_time": "2026-04-25T18:32:47.301252200Z" } }, "cell_type": "code", "source": [ "results_df = pd.DataFrame(results)\n", "results_df" ], "id": "b6d9827d298e4fa6", "outputs": [ { "data": { "text/plain": [ " Model MAE RMSE R2\n", "0 Linear Regression 0.280613 0.386712 0.146514\n", "1 Polynomial Regression 0.295032 0.415806 0.013258\n", "2 Ridge Regression 0.302947 0.416581 0.009580\n", "3 Lasso Regression 0.281669 0.387097 0.144814" ], "text/html": [ "
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ModelMAERMSER2
0Linear Regression0.2806130.3867120.146514
1Polynomial Regression0.2950320.4158060.013258
2Ridge Regression0.3029470.4165810.009580
3Lasso Regression0.2816690.3870970.144814
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" ] }, "execution_count": 901, "metadata": {}, "output_type": "execute_result" } ], "execution_count": 901 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:47.436110800Z", "start_time": "2026-04-25T18:32:47.323487900Z" } }, "cell_type": "code", "source": [ "results_melted = results_df.melt(\n", " id_vars='Model',\n", " value_vars=['MAE', 'RMSE', 'R2'],\n", " var_name='Metric',\n", " value_name='Score'\n", ")\n", "\n", "plt.figure(figsize=(9, 5))\n", "sns.barplot(data=results_melted, x='Model', y='Score', hue='Metric')\n", "plt.title(\"Part E: Regression Model Comparison (MAE, RMSE, R2)\")\n", "plt.xticks(rotation=15)\n", "plt.tight_layout()\n", "plt.show()" ], "id": "9e1241ab19a8fbea", "outputs": [ { "data": { "text/plain": [ "
" ], "image/png": 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FhMaAZRQFYQpAM5IuhPVeFJSoeqj+rQvaYJU5XeTrAje1sSa6KBUf1OjCKkhBaGoXk/Gfj/6WJLr4EI2RE41nUiqnAgF9R0o1VHqYqjj6anG68FZanC5olAKowFfBmy5SU6sMqLF0Sq3Sdx5PabBK/VPJeY298oKBhfj3mlrwmYguFnURrwtHBQJ6D6l9BvqclQYbP85G2+ef9/9XcKpAPCj+vSmoVMOA0lJ1S+079o0cB+O/IwUF6aHt1HuJ32/0GeiziA+W4z9vXxlSjTKJHo//HvS3ggG86HiXYDrwkTjOlR6qdFltq4ICVUfUPuu3x7/XRPuf9o/4KQ0UJPkxvsH9L737Xvw4xHhat35ztF/quNDvRFpBxAsvvOBSNfV+tF/5bVTqp1I249OP1eiQ0b9p+ntKpRSlJ+sz1/4bDNoT0e/CDTfc4NK9NV5Rr0uLglfd1KihwF1ptvqclDqs39JgkK7jNaPfpwJHpQ+r8qcaaR5//PGDjsXUuFsNE1CabqKqpsF9IrWAGAgjgjzgKKFxJBpTlogKClx22WVuHJXG1OgiWr0oEyZMSDFwXw52YZFsGpPhLz7Ua6MLSQVLGlfke1YU2CjAS21cTfxF5qGI/3z8+Cn1KAZLe3vBcvQqYKELKl2QqTVdAYrGMOmCR0GTLlJUJEJj8HTRp2VUdEWt3XosPvg5XKmVez/YBXSii0yN11IPmMZ2xQdxR4r/zNXjoX0gkfgA7GBBnoqZ6EL3UKT3ojK1zzujvocjeZyr90S9LsoMUI+xeszVWKExdyr0c6j+yVQDGseXnmBQ+6V63FUMSNvoe8gTfc7qCVNPWqIeKgVa6mnOqOMuNfGBo/9d07jitAoJ6ftW44+fQkbfVXr3d2U56KZ9RAWQFPSpkelICgaO+s3W+9Z4WhW7SnT+UuOUxiir8UO956n1tPt9ItF4PSCsSNcE4OZTUgutDxh00XOoLbRZuYVULe26OFGhCV8sRYUTlNqllCe91/ibKjuKT23yLfieXpvengX9LVFQmehvxaehann15umCWUGFUu4UxAWpl08T/CoVToGqioykNoG8AlZVBV2+fHnCVnAFXvE9RhlFF9Oaq1BzXqWVEqfPWT2e8QVFfHVO/z3o/1qfLybhxb8334ukC9REn7lu6U299HTRqcIniSZnTvR+9F58L663adMml7qbWsrc4dLfik9n1GcuvmBKRhznqVHAqHRMNU6ooI+CLe2f4t9rov1Pj2XkZ6HAx1cMTot6frTfq2Ekrf3Sz5+nQjVK8Q7eVAhGPYF6z5lNn7eK4qihJ62iSwrU1dOvFHAFbIcT5PjgKn6i8cyglFEdp3379k3xnH6DFeApeNU+najiref3CZ8ZABwNCPIAuNZSBWnBtBileB3KxYufUD21UvbJnELBT56ri4Jx48a5+2rR1vtVift4GoPn34emGVBPm68eGqz4mV5qdVfLuILMROPo/NQEen/xExQr4NNFjk+tU2AZ34ujyd8lvjR/8PvVxZDG7wRT9xRw+ImhfTpiRtP2a5oK9UaqNzk1SvFTr4oqcAa/B1UPVS+J70HQcno8+H3oe9RyQQqoFTw//fTTCS9OD2U6CE9VSZW2p6qZ+uziKQD0lUD9JNF670EjR450/09UYfSfCu6T2kd0X0Gu9uGMOs7jaV1Ke47/7NXr6fdHBQl6TFOtBPdRVbXUmKuM/Cw0rlENI6kdC572Ke1DGu+rnvODpWqqCq9SOoM39QSq5ymtKptHksah6nf3YGP91JutsW6ppS37357UGi/0PaWWbnukqYdVvZUK4pRi7KmxTseYxtWqB0/fQ1oWLVrk9v3guFcg7EjXBOAusnTxqUH6atVWCpLG8CmdTUUH0kMtxkpn0kW6xgJpzJrGSMTPx5QohSw+sJEaNWq4m+hiVWPQVKAkvcVX4qnXQtui99m1a1cXNOjiQcGHLh4UBOmCWD0vaqXXxbou5DQ2TnOfqSdNqU/6jDS1gC581Cqenh5MBVC6oNTYGBUxUOEb9a5pnIyKTqg3Ue9RPS+6IFcAqs9SwaVS4BRQ+PLuSptSqp16IhRAaYyYAlf9DR9YJKJxWCqKoIBOPS5atwIgXQwfbJzOPxWcOy6tsTjaHk2ZoAsy9T4pLVXz9SlQ8r1uuiDX56UULgUo+pyUFhgfaIj2Yb1fjfvUBbl69/RZ6mJWvTP6Hg+FPm8FxUo7VY+Axp1pn1JPq0qza7/x8yaqJ1gpcurtUYOB9jdNAaLvTz0rSj/LSOqh0zx2+psak6r9U/uW5uXzqccZcZzH0/6nqTJ0rOg9K3hSoRcV2fG9zzqulL6p4kf6HDTmS9+Dn5ZBPVIZRdNrqOFGPXA6ptOSaNqNIB0b6v1UD1hwLFqQfhP0PvRZ+vG9aoRQcJiIjlsFjcEe1mDDy6FQb6mfakXBcmq9VPpefGZCWkGeirIoQ0D7h3r2td+qAUC/0dpnlS4epGI9id6njhMfTGlMn7ZRKcHBOUUP9fdDvwEKZn22gqZZ0fGkHmm992BhGO2D2t4g/fbpd8NPGQQcFZJd3hPAkRUsHZ6W5557zpWVz5s3b6Rq1arudb7MdlB86fsglYBXmXOV7T7YdAoHm0Ih+NpDnUIhUQl0mThxYooy+88884zbZpWqV1l1lUrv1auXK7kdLNHfr1+/SMmSJd1yKjf//fffu2kobr311nR/1tp+lVFXyfl8+fJFKlWqFOnQoUPkiy++cM9v3brVfbb6/FXGXMvVr18/8vLLL0fXsXjx4kjbtm0j5cqVc9+VStNfcskl0XV4iT5/vVZ/X1MSFChQwJWND5btT+s9pGeaAUlUmj2RRPvRpk2b3BQLKk2vfUjfRfC78n799Vc3LUahQoXcZ6R/f/nllym+W9GUEe3atXPf3THHHBMpU6aM+7xeffXVQ35v3g8//OCmvShfvrzbTu0355xzTuSJJ56Ima5B5fVVEr5ChQrub5ctWzbSu3fvmGXS2mcTfUa+1Hxwmg1fYl/vVdOH6LstUaKE+y7279+f4cd5cN/as2dPpGfPnpGaNWu6z0HboX8/9dRTKV43bdo0NxWC/vbxxx/vpiTwU7jEv5d4ibYxNTVq1Ih06tTpsH4Hg9/Fa6+95l6jzyw1c+bMccs89thj0e1P63dN35+n/fzss88+6PtJ7TMRfeea2iQ4lUta311qx6n21XHjxrmpVvQZ6DvSfqTvS/uavuf0TqEQ3BYdE3pMU9OkJdF+HaTfSb1PTR8RnHYk0U3PBWnaFx2nzz77bJrbAIRNDv0n2YEmAGQ3auVWxT/1kGncCJAs6iFRr2f8OMWjlQocqbdePeWpFVRJtu+++85Vs1W10yORuptVKCtBPZXqdUsW9QIqW0Hp1Fm9aBiQkRiTBwAHoTm14vmxVoebPgrgyFAqn6akUCpqVqXUc6U0hjnAUx+CCr6oISxZNAZaKcoq3EKAh6MNPXkAcBAaV6KbxrxpvIfm9VJZdY35STQZMpCZ6MkDAMSj8AoAHIQKwKhQiVJ+NEmwL8aSzBZqAACA1NCTBwAAAAAhwpg8AAAAAAgRgjwAAAAACBHG5CVw4MABW79+vZt8Nz0THQMAAABAZlSu/eOPP6x06dKWM2fq/XUEeQkowCtbtuyR/H4AAAAA4LCsXbvWTjrppFSfJ8hLQD14/sMrVKjQ4X3yAAAAAJCBVOVbnVE+XkkNQV4CPkVTAR5BHgAAAICs5GBDyii8AgAAAAAhQpAHAAAAACFCkAcAAAAAIcKYPABAtrR//37bt29fsjcjdI455hjLlStXsjcDAPAPEOQBALLdHEEbN260bdu2JXtTQqtIkSJWsmRJ5ooFgGyKIA8AkK34AK948eJWoEABApEMDqB3795tmzdvdvdLlSqVkasHAGQSgjwAQLZK0fQB3gknnJDszQml/Pnzu/8r0NPnTOomAGQ/FF4BAGQbfgyeevBw5PjPlzGPAJA9EeQBAEI3CSz4fAHgaEaQBwAAAAAhQpAHAEAW66WcPn16sjcDAJCNEeQBABCnQ4cOLti69dZbU3w2Xbt2dc9pmfSYM2eOWz69Uz5s2LDBWrZsyXcCADhsBHkAACRQtmxZmzp1qv3555/Rx/766y+bMmWKlStXLsM/s71797r/a366vHnz8p0AAA4bQR4AAAmceeaZLtB7/fXXo4/p3wrwateuHX3swIEDNnToUKtQoYKbfqBmzZr26quvuudWr15tTZo0cf8uWrRoTA/g+eefb926dbPu3btbsWLFrHnz5gnTNdetW2dt27a1448/3goWLGh169a1zz77jO8MAJAq5skDACAVN954o02YMMGuu+46d3/8+PHWsWNHl4LpKcB74YUXbOzYsValShX76KOP7Prrr7cTTzzRGjVqZK+99pq1bt3ali9fboUKFYrOQyeTJk2yLl262CeffJLw7+/cudPOO+88K1OmjP3vf/9zvXyLFy92gSUAAKkhyAOATLBmcPVQfs7l+n9tYaZgrXfv3vbzzz+7+wrGlMLpg7w9e/bYgw8+aO+//741aNDAPVaxYkWbN2+ePf300y5AUw+caGLxIkWKxKxfQeGIESNS/ftKDd2yZYt9/vnn0fVUrlzZworjBAAyBkEeAACpUG/cxRdfbBMnTrRIJOL+rdRKb8WKFbZ792678MILU4yvC6Z0pqZOnTppPr9kyRK3Hh/gAQCQHgR5AAAcJGVTY+dk9OjRKdIp5a233nIplUHpKZ6iMXZpCaZ2AgCQXgR5AACkoUWLFq5nTgVRfHEUr1q1ai6YW7NmjUvNTCRPnjzu//v37z/kz7lGjRr27LPP2m+//UZvHgAg3aiuCQBAGnLlymXff/+9fffdd+7fQccdd5zdc889dtddd7kiKitXrnSFUZ544gl3X04++WQXIM6YMcONr/O9f+mhqpoqttKqVSs3HvCnn35yhVwWLFjAdwYASBVBHgAAB6GqmLolMmTIEOvXr5+rsnnaaae5nj+lb2pKBVEa56BBg+y+++6zEiVKRFM/00O9gO+++64r2nLRRRdZ9erVbdiwYSmCTQAAgnJENJIcMXbs2GGFCxe27du3p3pSB4BDQdXAjKHJyFetWuUCqHz58rEThuxz5jgBgIyJU+jJAwAAAIAQIcgDAAAAgBDJEkGeSlKXL1/epYTUr1/fFi5cmK7XaUJaDWbXgPQgZaD279/fSpUq5cpPN23a1H788ccjtPUAAAAAkHUkPcibNm2a9ejRwwYMGOAqktWsWdOVqN68eXOar1u9erWraNa4ceMUz40YMcIef/xxGzt2rH322WduHiKtU2MMAAAAACDMkh7kjRw50jp37mwdO3Z08w0pMCtQoICNHz8+1ddorqHrrrvOVSurWLFiil68UaNGWd++fe3yyy93cwxNnjzZ1q9fb9OnT8+EdwQAAAAAR2mQp8llFy1a5NIpoxuUM6e7n9YcQIMHD3blpDt16pTiOVUD27hxY8w6VYFGaaDMKwQAAAAg7HIn849v3brV9cpp3qAg3V+2bFnC18ybN8+ee+45W7JkScLnFeD5dcSv0z8Xb8+ePe4WLE0KAAAAANlR0tM1D8Uff/xhN9xwg40bN86KFSuWYevVBLbq7fO3smXLZti6AQAAAOCo6clToJYrVy7btGlTzOO6X7JkyRTLr1y50hVcufTSS6OPHThwwP0/d+7ctnz58ujrtA5V1wyus1atWgm3o3fv3q74S7Anj0APAAAAQHaU1J68PHnyWJ06dWz27NkxQZvuN2jQIMXyVatWta+//tqlavrbZZddZk2aNHH/VmBWoUIFF+gF16mgTVU2E61T8ubN62aMD94AAAAAIDtKak+eqAetffv2VrduXatXr56rjLlr1y5XbVPatWtnZcqUcSmVmkfvjDPOiHl9kSJF3P+Dj3fv3t0eeOABq1Kligv6+vXrZ6VLl04xnx4AIDzq9JycqX9v0UPtDmn5Dh062KRJk+yWW25xlaSDunbtak899ZQ7H06cODH6uAqGNWrUyFq0aGFvvfVWzGuU2aJzXCJ63dlnn31I2wcACI+kB3lt2rSxLVu2uMnLVRhFKZUzZ86MFk5Zs2aNq7h5KHr16uUCxZtvvtm2bdvmTpBap4JEAACSRRknU6dOtUcffdTy58/vHtMcrlOmTLFy5cqlWF6Fxm6//Xb3f00FpAbLeO+//76dfvrpMY+dcMIJR/BdAACyuqQHedKtWzd3S2TOnDlpvjbY4unlyJHDTbOgGwAAWcWZZ57pxpe//vrrbr5X0b8V4MX3yu3cudOmTZtmX3zxhWsE1fmuT58+KdapgC7ROHYAwNErW1XXBAAgu7vxxhttwoQJ0fvjx4+PDlEIevnll91Y9FNPPdWuv/56t1wkEsnkrQUAZEcEeQAAZCIFbJrz9eeff3a3Tz75xD0WTyma/nGNydu+fbvNnTs3xXINGza0Y489NuYGADi6ZYl0TQAAjhYnnniiXXzxxS79Uj1z+nf83K+aEmjhwoX2xhtvRKcJ0hh2BX7nn39+zLJK6TzttNMy9T0AALI2gjwAAJKQsunHoo8ePTrF8wrm/v7775hCKwoINeXPk08+aYULF44p5lK5cuVM2nIAQHZAkAcAQCZT+uXevXtdobDmzZvHPKfgbvLkyfbII49Ys2bNYp7TVEAvvfSS3XrrrZm8xQCykjWDq1sYlev/dbI3ITQI8vCP8CMDAIcuV65c9v3330f/HTRjxgz7/fffrVOnTjE9dtK6dWvXyxcM8n799VdXfTN+DlmmDQKAoxeFVwAASIJChQq5WzwFcU2bNk0R4PkgT1MqLF26NPqYli1VqlTMbfr06Ud8+wEAWRc9eQCAUFj0UDvLyhLN6xqUnsCsXr16MdMoMKUCACARevIAAAAAIEQI8gAAAAAgRAjyAAAAACBECPIAAAAAIEQI8gAAAAAgRAjyAAAAACBECPIAAAAAIEQI8gAAAAAgRAjyAAAAACBECPIAAAAAIERyJ3sDAADICGsGV8/UD7Jc/68PafkOHTrYpEmT3L9z585tJ510kl199dU2ePBgy5cvn3s8R44c7v8LFiyws88+O/raPXv2WOnSpe23336zDz/80M4//3z3+Ny5c23QoEG2ZMkS++uvv6xMmTLWsGFDGzdunOXJk8fmzJljTZo0Sbg9GzZssJIlSx72+wcAZF305AEAkElatGjhgquffvrJHn30UXv66adtwIABMcuULVvWJkyYEPPYG2+8Yccee2zMY999951bX926de2jjz6yr7/+2p544gkX3O3fvz9m2eXLl7u/G7wVL178CL5TAEAyEeQBAJBJ8ubN63rPFMi1atXKmjZtau+9917MMu3bt7epU6fan3/+GX1s/Pjx7vGgd999161rxIgRdsYZZ1ilSpVc0KdevPz588csq4BOywZvOXNyCQAAYcUvPAAASfDNN9/Y/PnzXc9bUJ06dax8+fL22muvuftr1qxxPXU33HBDzHIK1NQjp+cAAAgiyAMAIJPMmDHDpV1qDF716tVt8+bN1rNnzxTL3Xjjja73TiZOnGgXXXSRnXjiiTHLaDxf27Zt7bzzzrNSpUrZFVdcYU8++aTt2LEjxfo0/k9/199OP/30I/guAQDJRpAHAEAmUREUFUn57LPPXPplx44drXXr1imWu/76613xFY3dU5CnoC9erly53Ni9devWuZRNFV158MEHXQCnHr6gjz/+2P1df3v77beP6PsEACQXQR4AAJmkYMGCVrlyZatZs6brqVOw99xzz6VY7oQTTrBLLrnEOnXq5KpmtmzZMtV1KrhTKqd68b799lu3/NixY2OWqVChgvu7/nbyyScfkfcHAMgaCPIAAEjGCThnTuvTp4/17ds3psiKp947TYHQrl0712uXHkWLFnWpm7t27ToCWwwAyC6YJw8AgCTRuDqNyRs9erTdc889Mc+pUuaWLVusUKFCCV+r6ReUeqmxeKqsqR68yZMnu948TaUQpLF/ej6+t/CYY445Au8KAJBs9OQBAJAkmhS9W7dubkxdfO+bJkYvVqxYiuqbXr169Wznzp126623unF4KsDy6aef2vTp092/g0499VTXwxe8LVq06Ii+NwBA8tCTBwAIhXL9v7asTAVUErnvvvvcTSKRSKqvL1KkSMzztWvXtueffz7Nv3n++eenuU4AQDjRkwcAAAAAIUKQBwAAAAAhkiWCPA04L1++vJsctn79+rZw4cJUl3399detbt26Lm1Fpahr1aqVIl2lQ4cObixD8KYB7AAAAAAQdkkfkzdt2jTr0aOHm9NHAd6oUaOsefPmtnz5citevHiK5Y8//ni7//77rWrVqm4w+owZM9xkslpWr/MU1GmSWC9v3ryZ9p4AAAAA4KjtyRs5cqR17tzZBWrVqlVzwV6BAgXcJLGpDSJXuejTTjvNlYy+8847rUaNGjZv3ryY5RTUlSxZMnrT3EEAAAAAEHZJDfL27t3rSjg3bdr0/zYoZ053f8GCBQd9vSqGzZ492/X6nXvuuTHPaQJZ9e6pbHSXLl3s119/TXU9e/bssR07dsTcAAAAACA7Smq65tatW23//v1WokSJmMd1f9myZam+bvv27VamTBkXnOXKlcueeuopu/DCC2NSNa+88kqrUKGCrVy50vr06WMtW7Z0gaOWjzd06FAbNGhQBr87AAAAADgKx+QdjuOOO86WLFniJoFVT57G9FWsWNGlcso111wTXbZ69eounVOpnerdu+CCC1Ksr3fv3m4dnnryypYtm0nvBgAAAABCEuQVK1bM9axt2rQp5nHd1zi61Cils3Llyu7fqq75/fffu944H+TFUwCov7VixYqEQZ7G71GYBQAAAEAYJHVMnqpj1qlTx/XGeQcOHHD3GzRokO716DVK3UzNunXr3Ji8UqVK/eNtBgAAAICsLOnpmkqTbN++vZv7rl69em4KhV27drlqm9KuXTs3/k49daL/a1mlXyqwe/vtt908eWPGjHHPK4VT4+tat27tegM1Jq9Xr16u5y84xQIAIFzOeeKcTP17n9z+ySEtrzlcJ02a5P6dO3duO+mkk+zqq6+2wYMHu3liV69ebUOGDLEPPvjANm7caKVLl7brr7/eTRukRlEAALJNkNemTRvbsmWL9e/f353UlH45c+bMaDGWNWvWuPRMTwHgbbfd5nrn8ufP7+bLe+GFF9x6ROmfS5cudSfSbdu2uZNks2bN3ImTlEwAQDL5OVz37dvnqkurkTNHjhw2fPhwV3BMmSlPP/20a5j85ptv3BRDOu89/PDDfHEAgOwT5Em3bt3cLREVSwl64IEH3C01CvxmzZqV4dsIAMA/5edwFRX40pRB7733ngvyFADqFhxPrimClKlCkAcAyFaToQMAcDRST938+fPTTMXUlEHHH398pm4XACD7yxI9eQAAHA1mzJhhxx57rP39999uXLmGIzz55JMJl1VF6CeeeIJePADAISPIAwAgkzRp0sSlX2qc3aOPPuoKsKhQWLxffvnFpW6qMIvG5QEAcChI1wQAIJMULFjQFVWpWbOmjR8/3j777DN77rnnYpZZv369CwYbNmxozzzzDN8NAOCQEeQBAJAEStXs06eP9e3b1/78889oD97555/v5pBVFc5gdWkAANKLswcAAEmidExN/TN69OhogFeuXDk3Dk/TC2lqId0AADgUjMkDACBJNCZPUwiNGDHCTQGkYiu6aaL0oEgkwncEAEg3gjwAQCh8cvsnlpVNnDgx4eP33Xefu0nXrl0zeasAAGFEuiYAAAAAhAhBHgAAAACECEEeAAAAAIQIQR4AAAAAhAhBHgAg26HaJJ8vACB1BHkAgGzjmGOOcf/fvXt3sjcl1Pzn6z9vAED2whQKAIBsQxOHFylSxDZv3uzuFyhQwHLkyJHszQpVD6kCPH2++pz1eQMAsh+CPABAtlKyZEn3fx/oIeMpwPOfMwAg+yHIAwBkK+q5K1WqlBUvXtz27duX7M0JHaVo0oMHANkbQR4AIFtSIEIwAgBAShReAQAAAIAQIcgDAAAAgBAhyAMAAACAECHIAwAAAIAQIcgDAAAAgBAhyAMAAACAECHIAwAAAIAQIcgDAAAAgBAhyAMAAACAECHIAwAAAIAQIcgDAAAAgBAhyAMAAACAEMkSQd7o0aOtfPnyli9fPqtfv74tXLgw1WVff/11q1u3rhUpUsQKFixotWrVsueffz5mmUgkYv3797dSpUpZ/vz5rWnTpvbjjz9mwjsBAAAAgKM8yJs2bZr16NHDBgwYYIsXL7aaNWta8+bNbfPmzQmXP/744+3++++3BQsW2NKlS61jx47uNmvWrOgyI0aMsMcff9zGjh1rn332mQsGtc6//vorE98ZAAAAAGS+3JZkI0eOtM6dO7tATRSYvfXWWzZ+/Hi77777Uix//vnnx9y/8847bdKkSTZv3jwXyKkXb9SoUda3b1+7/PLL3TKTJ0+2EiVK2PTp0+2aa67JpHcGAMCRUafn5FB+tG8cl+wtAIBwSGpP3t69e23RokUunTK6QTlzuvvqqTsYBXSzZ8+25cuX27nnnuseW7VqlW3cuDFmnYULF3ZpoOlZJwAAAABkZ0ntydu6davt37/f9bIF6f6yZctSfd327dutTJkytmfPHsuVK5c99dRTduGFF7rnFOD5dcSv0z8XT+vRzduxY8c/el8AAAAAcNSmax6O4447zpYsWWI7d+50PXka01exYsUUqZzpNXToUBs0aFCGbycAAAAAHFXpmsWKFXM9cZs2bYp5XPdLliyZ6uuU0lm5cmVXWfPuu++2q666ygVq4l93KOvs3bu36x30t7Vr12bAuwMAAACAoyzIy5Mnj9WpU8f1xnkHDhxw9xs0aJDu9eg1Pt2yQoUKLpgLrlPpl6qymdo68+bNa4UKFYq5AQAAAEB2lPR0TaVatm/f3s19V69ePVcZc9euXdFqm+3atXPj73xPnf6vZStVquQCu7ffftvNkzdmzBj3fI4cOax79+72wAMPWJUqVVzQ169fPytdurS1atUqqe8VAAAAAEIf5LVp08a2bNniJi9XYRSlYM6cOTNaOGXNmjUuPdNTAHjbbbfZunXr3ETnVatWtRdeeMGtx+vVq5db7uabb7Zt27ZZo0aN3Do12TqArI3S8AAAANk8yJNu3bq5WyJz5syJua8eOt3Sot68wYMHuxsAAAAAHE2SOiYPAAAAAJCxCPIAAAAAIEQI8gAAAAAgRAjyAAAAACBECPIAAAAAIEQI8gAAAAAgRAjyAAAAACBECPIAAAAAIEQI8gAAAAAgRHInewMAAACAI6FOz8mh/GDfOC7ZW4CsjiAvk/AjAwAAACAzkK4JAAAAACFCkAcAAAAAIUKQBwAAAAAhQpAHAAAAACFCkAcAAAAAIUKQBwAAAAAhQpAHAAAAACFCkAcAAAAAIUKQBwAAAAAhQpAHAAAAACFCkAcAAAAAIUKQBwAAAAAhQpAHAAAAACFCkAcAAAAAIUKQBwAAAAAhQpAHAAAAACFCkAcAAAAAIUKQBwAAAAAhQpAHAAAAACFCkAcAAAAAIZIlgrzRo0db+fLlLV++fFa/fn1buHBhqsuOGzfOGjdubEWLFnW3pk2bpli+Q4cOliNHjphbixYtMuGdAAAAAMBRHuRNmzbNevToYQMGDLDFixdbzZo1rXnz5rZ58+aEy8+ZM8fatm1rH374oS1YsMDKli1rzZo1s19++SVmOQV1GzZsiN5eeumlTHpHAAAAAHAUB3kjR460zp07W8eOHa1atWo2duxYK1CggI0fPz7h8i+++KLddtttVqtWLatatao9++yzduDAAZs9e3bMcnnz5rWSJUtGb+r1AwAAAICwS2qQt3fvXlu0aJFLuYxuUM6c7r566dJj9+7dtm/fPjv++ONT9PgVL17cTj31VOvSpYv9+uuvGb79AAAAAJDV5E7mH9+6davt37/fSpQoEfO47i9btixd67j33nutdOnSMYGiUjWvvPJKq1Chgq1cudL69OljLVu2dIFjrly5Uqxjz5497ubt2LHjH70vAAAAADgqg7x/atiwYTZ16lTXa6eiLd4111wT/Xf16tWtRo0aVqlSJbfcBRdckGI9Q4cOtUGDBmXadgMAAABAKNM1ixUr5nrWNm3aFPO47mscXVoefvhhF+S9++67LohLS8WKFd3fWrFiRcLne/fubdu3b4/e1q5dexjvBgAAAACO8iAvT548VqdOnZiiKb6ISoMGDVJ93YgRI2zIkCE2c+ZMq1u37kH/zrp169yYvFKlSiV8XkVaChUqFHMDAAAAgOwo6dU1NX2C5r6bNGmSff/9965Iyq5du1y1TWnXrp3rafOGDx9u/fr1c9U3Nbfexo0b3W3nzp3uef2/Z8+e9umnn9rq1atdwHj55Zdb5cqV3dQMAAAAABBmSR+T16ZNG9uyZYv179/fBWuaGkE9dL4Yy5o1a1zFTW/MmDGuKudVV10Vsx7Nszdw4ECX/rl06VIXNG7bts0VZdE8eur5U48dAAAAAIRZ0oM86datm7slomIpQeqdS0v+/Plt1qxZGbp9AAAAAJBdJD1dEwAAAACQcQjyAAAAACBE/lGQp7Fxy5cvt7///jvjtggAAAAAkLlB3u7du61Tp05WoEABO/30011xFLn99tvd3HUAAAAAgGwU5GlKg6+++soVRcmXL1/08aZNm9q0adMycvsAAAAAAEe6uub06dNdMHf22Wdbjhw5oo+rV2/lypWHs0oAAAAAQLJ68jSvXfHixVM8rknMg0EfAAAAACAbBHl169a1t956K3rfB3bPPvusNWjQIOO2DgAAAABw5NM1H3zwQWvZsqV99913rrLmY4895v49f/58mzt37uGsEgAAAACQrJ68Ro0aucIrCvCqV69u7777rkvfXLBggdWpUycjtgsAAAAAkBk9efv27bNbbrnF+vXrZ+PGjTucvwkAAAAAyCo9ecccc4y99tprR2ZrAAAAAACZn67ZqlUrN40CAAAAACAEhVeqVKligwcPtk8++cSNwStYsGDM83fccUdGbR8AAAAA4EgHec8995wVKVLEFi1a5G5Bmk6BIA8AAAAAslGQt2rVqozfEgAAAABAcsbkBUUiEXcDAAAAAGTjIG/y5Mlujrz8+fO7W40aNez555/P2K0DAAAAABz5dM2RI0e6efK6detm55xzjnts3rx5duutt9rWrVvtrrvuOpzVAgAAAACSEeQ98cQTNmbMGGvXrl30scsuu8xOP/10GzhwIEEeAAAAAGSndM0NGzZYw4YNUzyux/QcAAAAACAbBXmVK1e2l19+OcXj06ZNc3PoAQAAAACyUbrmoEGDrE2bNvbRRx9Fx+RpYvTZs2cnDP4AAAAAAFm4J69169b22WefWbFixWz69Onupn8vXLjQrrjiiozfSgAAAADAkevJkzp16tgLL7xwuC8HAAAAAGSVnry3337bZs2aleJxPfbOO+9kxHYBAAAAADIryLvvvvts//79KR6PRCLuOQAAAABANgryfvzxR6tWrVqKx6tWrWorVqzIiO0CAAAAAGRWkFe4cGH76aefUjyuAK9gwYKHs0oAAAAAQLKCvMsvv9y6d+9uK1eujAnw7r77brvssssyYrsAAAAAAJkV5I0YMcL12Ck9s0KFCu6mf59wwgn28MMPH84qAQAAAADJTNecP3++vfXWW3bbbbe5HrwPP/zQPvjgAytSpMghr2/06NFWvnx5y5cvn9WvX9/Nt5eacePGWePGja1o0aLu1rRp0xTLqwBM//79rVSpUpY/f363jMYRAgAAAEDYHVKQt2DBApsxY4b7d44cOaxZs2ZWvHhx13unCdJvvvlm27NnzyFtwLRp06xHjx42YMAAW7x4sdWsWdOaN29umzdvTrj8nDlzrG3bti6o1PaULVvWbccvv/wS09P4+OOP29ixY92k7ep11Dr/+uuvQ9o2AAAAAAh1kDd48GD79ttvo/e//vpr69y5s1144YVu6oQ333zThg4dekgbMHLkSLeOjh07uoqdCswKFChg48ePT7j8iy++6HoPa9Wq5VJEn332WTtw4IDNnj072os3atQo69u3rxs7WKNGDZs8ebKtX7/epk+ffkjbBgAAAAChDvKWLFliF1xwQfT+1KlTrV69ei6FUr1x6j17+eWX072+vXv32qJFi1w6ZXSDcuZ099VLlx67d++2ffv22fHHH+/ur1q1yjZu3BizTqWXKg00tXWq93HHjh0xNwAAAAAIfZD3+++/W4kSJaL3586day1btozeP+uss2zt2rXpXt/WrVvdpOrBdYruK1BLj3vvvddKly4dDer86w5lnep9VCDob0oBBQAAAIDQB3kKlNRT5nvhNIbu7LPPjj7/xx9/2DHHHGOZZdiwYa438Y033nBFWw5X7969bfv27dHboQSqAAAAAJBtg7yLLrrIjb37+OOPXWCksXOqdOktXbrUKlWqlO71FStWzHLlymWbNm2KeVz3S5YsmeZrVexFQd67777rxt15/nWHss68efNaoUKFYm4AAAAAEPogb8iQIZY7d24777zz3Dg83fLkyRN9XsVSVOkyvfTaOnXqRIumiC+i0qBBg1Rfp+qZ2paZM2da3bp1Y57TnH0K5oLr1Bg7VdlMa50AAAAAEAa5D2Vh9bx99NFHLqXx2GOPdb1wQa+88op7/FCoYEv79u1dsKYiLqqMuWvXLldtU9q1a2dlypSJVu0cPny4mwNvypQpbm49P85Of1c3Te3QvXt3e+CBB6xKlSou6OvXr58bt9eqVatD2jYAAAAACHWQ56k4SSK+wuWhaNOmjW3ZssUFbgrYNDWCeuh84ZQ1a9a4ipvemDFj3HjAq666KmY9mmdv4MCB7t+9evVygaLm7du2bZs1atTIrfOfjNsDAAAAgNAGeRmtW7du7pba5OdBq1evPuj61JunOf10AwAAAICjySGNyQMAAAAAZG0EeQAAAAAQIgR5AAAAABAiBHkAAAAAECIEeQAAAAAQIgR5AAAAABAiBHkAAAAAECIEeQAAAAAQIgR5AAAAABAiBHkAAAAAECIEeQAAAAAQIgR5AAAAABAiBHkAAAAAECIEeQAAAAAQIgR5AAAAABAiBHkAAAAAECIEeQAAAAAQIgR5AAAAABAiBHkAAAAAECIEeQAAAAAQIgR5AAAAABAiBHkAAAAAECIEeQAAAAAQIgR5AAAAABAiBHkAAAAAECIEeQAAAAAQIgR5AAAAABAiBHkAAAAAECIEeQAAAAAQIgR5AAAAABAiSQ/yRo8ebeXLl7d8+fJZ/fr1beHChaku++2331rr1q3d8jly5LBRo0alWGbgwIHuueCtatWqR/hdAAAAAEDWkNQgb9q0adajRw8bMGCALV682GrWrGnNmze3zZs3J1x+9+7dVrFiRRs2bJiVLFky1fWefvrptmHDhuht3rx5R/BdAAAAAEDWkdQgb+TIkda5c2fr2LGjVatWzcaOHWsFChSw8ePHJ1z+rLPOsoceesiuueYay5s3b6rrzZ07twsC/a1YsWJH8F0AAAAAQNaRtCBv7969tmjRImvatOn/bUzOnO7+ggUL/tG6f/zxRytdurTr9bvuuutszZo1GbDFAAAAAJD1JS3I27p1q+3fv99KlCgR87jub9y48bDXq3F9EydOtJkzZ9qYMWNs1apV1rhxY/vjjz9Sfc2ePXtsx44dMTcAAAAAyI5yW8i0bNky+u8aNWq4oO/kk0+2l19+2Tp16pTwNUOHDrVBgwZl4lYCAAAAQMh68jROLleuXLZp06aYx3U/raIqh6pIkSJ2yimn2IoVK1Jdpnfv3rZ9+/bobe3atRn29wEAAADgqAjy8uTJY3Xq1LHZs2dHHztw4IC736BBgwz7Ozt37rSVK1daqVKlUl1GRVwKFSoUcwMAAACA7Cip6ZqaPqF9+/ZWt25dq1evnpv3bteuXa7aprRr187KlCnj0il9sZbvvvsu+u9ffvnFlixZYscee6xVrlzZPX7PPffYpZde6lI0169f76ZnUI9h27Ztk/hOkd2c88Q5Fkaf3P5JsjcBAAAAYQ7y2rRpY1u2bLH+/fu7Yiu1atVyBVN8MRZVxVTFTU9BW+3ataP3H374YXc777zzbM6cOe6xdevWuYDu119/tRNPPNEaNWpkn376qfs3AAAAgKyJRvYQFV7p1q2buyXiAzevfPnyFolE0lzf1KlTM3T7AAAAACA7Sepk6AAAAACAjEWQBwAAAAAhQpAHAAAAACFCkAcAAAAAIUKQBwAAAAAhQpAHAAAAACFCkAcAAAAAIUKQBwAAAAAhQpAHAAAAACFCkAcAAAAAIUKQBwAAAAAhQpAHAAAAACFCkAcAAAAAIUKQBwAAAAAhQpAHAAAAACFCkAcAAAAAIUKQBwAAAAAhQpAHAAAAACFCkAcAAAAAIUKQBwAAAAAhQpAHAAAAACFCkAcAAAAAIUKQBwAAAAAhQpAHAAAAACFCkAcAAAAAIUKQBwAAAAAhQpAHAAAAACFCkAcAAAAAIUKQBwAAAAAhQpAHAAAAACFCkAcAAAAAIZL0IG/06NFWvnx5y5cvn9WvX98WLlyY6rLffvuttW7d2i2fI0cOGzVq1D9eJwAAAACESVKDvGnTplmPHj1swIABtnjxYqtZs6Y1b97cNm/enHD53bt3W8WKFW3YsGFWsmTJDFknAAAAAIRJUoO8kSNHWufOna1jx45WrVo1Gzt2rBUoUMDGjx+fcPmzzjrLHnroIbvmmmssb968GbJOAAAAAAiTpAV5e/futUWLFlnTpk3/b2Ny5nT3FyxYkGXWCQAAAADZSe5k/eGtW7fa/v37rUSJEjGP6/6yZcsydZ179uxxN2/Hjh2H9fcBAAAAwI72witZwdChQ61w4cLRW9myZZO9SQAAAACQvYK8YsWKWa5cuWzTpk0xj+t+akVVjtQ6e/fubdu3b4/e1q5de1h/HwAAAACO2iAvT548VqdOHZs9e3b0sQMHDrj7DRo0yNR1qohLoUKFYm4AAAAAkB0lbUyeaKqD9u3bW926da1evXpu3rtdu3a5ypjSrl07K1OmjEun9IVVvvvuu+i/f/nlF1uyZIkde+yxVrly5XStEwAAAADCLKlBXps2bWzLli3Wv39/27hxo9WqVctmzpwZLZyyZs0aVx3TW79+vdWuXTt6/+GHH3a38847z+bMmZOudQIAAABAmCU1yJNu3bq5WyI+cPPKly9vkUjkH60TAAAAAMKM6poAAAAAECIEeQAAAAAQIgR5AAAAABAiBHkAAAAAECIEeQAAAAAQIgR5AAAAABAiBHkAAAAAECIEeQAAAAAQIgR5AAAAABAiBHkAAAAAECIEeQAAAAAQIgR5AAAAABAiBHkAAAAAECIEeQAAAAAQIgR5AAAAABAiBHkAAAAAECIEeQAAAAAQIgR5AAAAABAiBHkAAAAAECIEeQAAAAAQIgR5AAAAABAiBHkAAAAAECIEeQAAAAAQIgR5AAAAABAiBHkAAAAAECIEeQAAAAAQIgR5AAAAABAiBHkAAAAAECIEeQAAAAAQIgR5AAAAABAiBHkAAAAAECJZIsgbPXq0lS9f3vLly2f169e3hQsXprn8K6+8YlWrVnXLV69e3d5+++2Y5zt06GA5cuSIubVo0eIIvwsAAAAASL6kB3nTpk2zHj162IABA2zx4sVWs2ZNa968uW3evDnh8vPnz7e2bdtap06d7Msvv7RWrVq52zfffBOznIK6DRs2RG8vvfRSJr0jAAAAADiKg7yRI0da586drWPHjlatWjUbO3asFShQwMaPH59w+ccee8wFcD179rTTTjvNhgwZYmeeeaY9+eSTMcvlzZvXSpYsGb0VLVo0k94RAAAAABylQd7evXtt0aJF1rRp0//boJw53f0FCxYkfI0eDy4v6vmLX37OnDlWvHhxO/XUU61Lly7266+/prode/bssR07dsTcAAAAACA7SmqQt3XrVtu/f7+VKFEi5nHd37hxY8LX6PGDLa+evsmTJ9vs2bNt+PDhNnfuXGvZsqX7W4kMHTrUChcuHL2VLVs2Q94fAAAAAGS23BZC11xzTfTfKsxSo0YNq1Spkuvdu+CCC1Is37t3bzcu0FNPHoEeAAAAgOwoqT15xYoVs1y5ctmmTZtiHtd9jaNLRI8fyvJSsWJF97dWrFiR8HmN3ytUqFDMDQAAAACyo6QGeXny5LE6deq4tErvwIED7n6DBg0SvkaPB5eX9957L9XlZd26dW5MXqlSpTJw6wEAAAAg60l6dU2lSY4bN84mTZpk33//vSuSsmvXLldtU9q1a+fSKb0777zTZs6caY888ogtW7bMBg4caF988YV169bNPb9z505XefPTTz+11atXu4Dw8ssvt8qVK7sCLQAAAAAQZkkfk9emTRvbsmWL9e/f3xVPqVWrlgvifHGVNWvWuIqbXsOGDW3KlCnWt29f69Onj1WpUsWmT59uZ5xxhnte6Z9Lly51QeO2bdusdOnS1qxZMzfVgtIyAQAAACDMkh7kiXrhfE9cPBVLiXf11Ve7WyL58+e3WbNmZfg2AgAAAEB2kPR0TQAAAABAxiHIAwAAAIAQIcgDAAAAgBAhyAMAAACAECHIAwAAAIAQIcgDAAAAgBAhyAMAAACAECHIAwAAAIAQIcgDAAAAgBAhyAMAAACAECHIAwAAAIAQIcgDAAAAgBAhyAMAAACAECHIAwAAAIAQIcgDAAAAgBAhyAMAAACAECHIAwAAAIAQIcgDAAAAgBAhyAMAAACAECHIAwAAAIAQIcgDAAAAgBAhyAMAAACAECHIAwAAAIAQIcgDAAAAgBDJnewNAABkX+c8cY6F0Se3f5LsTQAA4LDRkwcAAAAAIUKQBwAAAAAhQromAADAEURaM4DMRk8eAAAAAIQIQR4AAAAAhEiWCPJGjx5t5cuXt3z58ln9+vVt4cKFaS7/yiuvWNWqVd3y1atXt7fffjvm+UgkYv3797dSpUpZ/vz5rWnTpvbjjz8e4XcBAAAAAMmX9CBv2rRp1qNHDxswYIAtXrzYatasac2bN7fNmzcnXH7+/PnWtm1b69Spk3355ZfWqlUrd/vmm2+iy4wYMcIef/xxGzt2rH322WdWsGBBt86//vorE98ZAAAAAByFQd7IkSOtc+fO1rFjR6tWrZoLzAoUKGDjx49PuPxjjz1mLVq0sJ49e9ppp51mQ4YMsTPPPNOefPLJaC/eqFGjrG/fvnb55ZdbjRo1bPLkybZ+/XqbPn16Jr87AAAAADiKgry9e/faokWLXDpldINy5nT3FyxYkPA1ejy4vKiXzi+/atUq27hxY8wyhQsXdmmgqa0TAAAAAMIiqVMobN261fbv328lSpSIeVz3ly1blvA1CuASLa/H/fP+sdSWibdnzx5387Zv3+7+v2PHDsso+/f8aWH0xzH7LYz+/vNvC6OM3KePFI6V7IVjJTk4TrIXjpPk4VjJXjhW0n8tp+zFtDBPnpkNHTrUBg0alOLDKVu2bDo+6qPbGcneABySwvcW5hNLEo6V7IVjJTk4TrIXjpPk4VjJXgofgeuvP/74w2UrZskgr1ixYpYrVy7btGlTzOO6X7JkyYSv0eNpLe//r8dUXTO4TK1atRKus3fv3q74i3fgwAH77bff7IQTTrAcOXL8g3eIjGy1UNC9du1aK1SoEB8swLECcE4BjjCuv7Ie9eApwCtdunSayyU1yMuTJ4/VqVPHZs+e7Spk+gBL97t165bwNQ0aNHDPd+/ePfrYe++95x6XChUquEBPy/igTjuoqmx26dIl4Trz5s3rbkFFihTJsPeJjKMAjyAP4FgBOKcAmYfrr6wlrR68LJOuqR609u3bW926da1evXquMuauXbtctU1p166dlSlTxqVUyp133mnnnXeePfLII3bxxRfb1KlT7YsvvrBnnnnGPa+eNwWADzzwgFWpUsUFff369XPRrg8kAQAAACCskh7ktWnTxrZs2eImL1dhFPW+zZw5M1o4Zc2aNa7iptewYUObMmWKmyKhT58+LpDT1AhnnPF/2cm9evVygeLNN99s27Zts0aNGrl1avJ0AAAAAAizHJGDlWYBsgBVP1VvrsZPxqfWAuBYATinAFx/4f8Q5AEAAABAiCR1MnQAAAAAQMYiyAMAAACAECHIAwAAAIAQIcgDAAAAgBAhyAOS7MCBA7Z///5kbwYQSiogzfGFo2E///vvv935BEDqjqZrLqprAkn6kcmRI4e7AcgcmzZtcvOlFi5c2F0Uc/whDOeS4FzCwr4NpDxOJP5YCbuj690CSaATbvx0lPqh8ReY77//vt1www3Wrl07++yzz/iOgAzqwdi1a5etWrXKnnvuOTvxxBOtbt261rFjR/vll18I8JDtaB9PdC6RLVu2uHlkGzRoYLfeeqv9/PPPSdpKIPkSHSc5/9+xsmjRIrvnnnvccfLdd99ZmBHkAf/Qvn37bNq0aTZ+/Hh336cB+IvORD12W7dutbPPPtteeeUVGzVqlOtd0Em6WbNm9vnnn/OdAHEGDx5s//rXv1KcvHVs5c6dO0ULrY7Lpk2b2k033WSffPKJTZw40V566SX76KOPbNiwYbZt2zY+Y2QpCszU4Ldy5cqYx/0+H2wc9J5++mm74oorbPjw4a7xok2bNvbhhx9a165dbcWKFZm6/UBm0PGgxvGXX3455lor2AiS6Jrr4osvtrfeessefPBB1/j39ddf2yWXXOKOF7/esCHIA/6hnTt32jfffBP9UcmVK9f/f3D9v4vOZcuW2eTJk12Lkf8xUrrY+vXr7brrrrNrr73Wxo0bZ1OnTrXatWu7oC+MPzbAP6GL1yeffDLFyfunn36yfv36WZMmTax79+72ww8/uJ69Y445xvXczZs3z+rUqeNO8I0aNXLLfvnll7Z48WK+EGQpJ5xwgttvjzvuuJjHtc/rInXSpEn2+OOPu2DO0zll4cKFLgtEjRc6BkaOHOkaMf73v/8l4V0AR9bu3bvtjTfesN9++y3mWss3gqjBXMHcqlWrotdSOieo8aR169bWokULe+211+zFF1+0ihUrumMqrAjygH9YzKFo0aI2ZMgQlwYW9P3337sLz7POOstGjBhhl156qfu/Tso6kbds2dIqVKjgeu984Hf99dfbBx98YBs2bOB7wVFLx0h8Cuapp55q1apVsz179kQfW7duneupU0ts8+bNbcGCBXbVVVfZO++8454/88wzrXTp0lamTJnoa5TOpuOXIA9Z5TziL0QLFizoMkKKFy8es9wzzzzj9v9HHnnENRhedNFF7v+ijBCdg/S89nW/j5crV87mz5+fhHcFZDwdI/58oONk9OjRLt0yvsFPPXNly5a122+/3Vq1auUaPnwDioK7kiVLuoZ1KV++vOs5nzNnjkvtD+MYbYI84BAEUzB9j52olVU/JrNnz3b3deJ+6qmn7K+//nIpM0rB7NSpkz377LPucWncuLFt3LjRXcx6+hFScYgff/yR7wVHLbXI+hRMpV36BhU1jNx1113R5Z544gnXWqtW3fvuu8+lPysQHDBggHu+fv367gJYJ3+vevXq7jE1wgDJEEwp03nEX1zq/2qgUMOFzimilDKll9177722dOlSl6J23nnnWY8ePdz5xTd+bN++Pbp+XdBWqVLF1q5d684nQBiuuYIp+eqpnjBhQsw1l+6r4W/58uWud7tNmzb20EMP2ZQpU1zDus4HuuYKBnMNGzZ02VhfffWVhRFBHpAK/WjEl9n1PzL6AfnPf/5jL7zwgruvE6lOvrrI9GMr1Dr073//20qUKGH58+d3g+LPPfdce/PNN90yF1xwgWs98gN/deI/6aST7OSTT3YpZsDRdnz5i98vvvjCunXr5gKyDh06uHRo0QWteifUMPLnn3+6i1iduFVURa9V70WXLl3c8jrZ6+K3WLFiLmVaF8SiY/G0005zveXxY5+AI9Ur7fftYOVLNT48+uijduedd9rMmTOjx4V687T/ihoxFPD17NnT3Vd62dChQ92F6auvvmoFChSwqlWruovX4P6sfV9/izHeyM5TG/hrLh0rfliL6Ph47LHH7PXXX3f3f/31Vzfmun379u4aSr/7ffr0cY3puubS+ULnCvn000+j69c5Q+eVWbNmWRgR5AFx/MlYLazB3jpRWljlypVd6qVakHRS/eOPP9yJVz8mvndA6WEaG6TW1OCJXWPulEeu50qVKmWnnHKKG0AcpPUoYFQACIRV8PjSBapPl1FhFKXQbN682RWPaNu2bfSYvPLKK12jiE7wefPmdRfPusjVCVyv1XIK4NRq6wPD008/3QWDulj2dFGsY1Bj84DM6JXW/umnzlHKsRojdNGpol16XuOIROlmefLkie6/aozQRav2YdFrla6mc4kKCskZZ5zheryDKcg6DvS3NDYJyMqChYXir7kUkNWsWdNq1arlMqE+/vhj97uvRgyNudb4VB0TSnHWMeKvuXyGVMOGDaMNehoeo/PBf//73+jf1Xnk/PPPjwaPYUOQh6NWapMk68So1Jfnn3/e9SL4FlS1nKrCnwI8FU3R2Dn1Nhx77LGud0CtQerR08WjfjjUQqTB8MGWWy2rv7l3795oeqZacHWC9ssoX1xjiYCwTm2gY0BFITS2SCdnFSBSuoweV3EJnYzV0KExF7ro1QledGGrSrQ60euCQI0rq1evjpaL1zGkAFDr9OlrGrOk9GeVzfZUhEXVNi+77LJM+zwQ7vNIapOQqzFQ+7F+69XT4DNB1HOgHgZdxGqs3dVXXx292FXQpvOLaAxRoUKFotPr+ItgHSM6D/nldW4JZoBUqlTJZZJorCqQ1cbVBfkGunfffdd69eplffv2dY/rumjQoEGuYNaaNWvcMaC0fC2r3381kuuay2dDKfDTucGv0x8nCvLUcKLHVANBfydIwwB0LvHZHmFCkIejVvy4Om/u3LmuWIrGQeiCUj8O6n3TSVQ/IEoh0wWkgrnjjz8++mOiIE/Bnnoi5PLLL3djhZR6Fly3Lnx1UhaVhNeYvd9//z26jC4GlFuu1logu84HGZzaIDjuVNSDpiqXOkmrBVXHmo4lHY86sWt5VZlVeXhdJGuMhXrrVHVQlTJ9aptOzupJV+OLP4Y0/kJjkjRuyfeMawC+WnA9XTjrwkHHNpAR55FEkyzfdtttbnydzhcXXnihO5+IMj50PlGVQJ1Hvv32W9cw6I8fNULoXKPXqcFP+7PmehQdUxqbp148nT/8uUeZIdqGYHGKu+++2+37QLL5xu5Ex4n2ZfXWqXideuM03k4928rIUDEtPVekSBHXmKeiKnpcdC2m9fprLDXa6fdfWRv+2u7TTz91jeo61/hGP51PdGz5azcdbxoL64/PUIkAIXbgwIHI/v373f/jffnll5EHH3wwMnTo0MjGjRujjzdq1Chy2223Re/v2rUr+u/evXtHTjzxxMjJJ58cueyyyyINGjSIdOrUKfLHH39ENmzYELnkkksi119/vVt25cqVkRYtWkTKlCkTGTVqVKRDhw6RqlWrRt56663o+rRtifz9998JtxnISrSPal9N5Jdffon069cvcsYZZ0Tq1q0bGTx4cGTz5s3uufbt20eaN2+e8HU//PBD5Nprr42cddZZkauvvjpSpUqVSKlSpSLDhg1zz+uYLV++fOTPP/9092fNmhUpW7ZspE6dOpGTTjrJ/full15K17YD6eF/p4O/137/0e/+448/7n73J0+eHNm0aZN7/IMPPohUq1Yt8uabb6ZYz4oVKyI33nhjJHfu3JH69etHLrjggsgpp5wS6dOnj3t+8eLFkRw5ckQ+/fRTd//zzz+PFCxYMNK0adPIXXfdFaldu3akZcuWkZ07d0bXvW/fvoTbntrxCRwp2s8TXdusWbMm8swzz0SeeuqpyJYtW6KP61rqhhtuiN7ftm1bzDVX4cKFIxUrVoy0bt06cuGFF0a6dOninlu/fr27xrrlllvcfa1T55pTTz01MmHChEivXr3ccfXqq69G16fzRvCa7mDbnN3l0H+SHWgCGSWYGhlPLUQq0KDWmjvuuMP1IKhXQK2pGrSrQirqfdNjuiltQKlfaiVVS6pa/dVroLQB/V+tRUoVGDt2rEs3U8+EBvqq58Gn1mhc0ZgxY+y9995zLa2qsKn0mfhtTGu7gaxEvWzqTYintEmlQCpFTGkzKmGtHgdNC6JB8EqzUeEh9c6p4pnSMTVuSGWslVKjY/Occ85xx1rwmFWLrOYx0pxGuq+0TqVtqvXWpzVrXIZaYlVCXuk48dvnexkTtSID8dL6Pd6xY4fb37TvqqiJxtb5HgJlaqinQan+6q1Wqv8111zj9lOtT2NBdSzoHKTeCo0l0lgh9VrofKKKmTqn6FhQz4Wm5tH6tT+ryqYKfamIUNOmTd05R73f8dstnEuQFai3TL1uGjd9//33u8ri6lHz89npnKDeN42J0/AWTYugXm6lGvvzgMZq6zdfw2XUk6esKp0/lNKpOSF1LadsKB0bOh5UoEXnGKVDFy1a1PWk65zke/+OumuuZEeZQEb0JCRqld+zZ0/km2++ibz77ruRc8891/UGfPvtt5Hnn3/e9S5899130WV79uzpHlMrz4wZM1zvm24XXXSRaxWqXr2662FIpEKFCpEhQ4a4f6uFqnjx4pGvvvoq+nwYW4dw9NDxlVpvgHrm1Os9ZcqUSLt27Vyv26JFi1zvhXooVq9eHV129OjR7tgYN26cOyZGjBjhWmbVCnveeedFihUrFrnpppvcsnv37o32Uvz111+Ryy+/3PV86N/aFh2P7733XqrbzDGHjNzPlyxZEvnoo49cT5162Lp27eqyP9T7oF5p7+eff3a9cp07d3b3H3roocjxxx8fady4caRZs2aR4447LnLNNde4c1M8nXeOPfbYyMKFC9199UhcddVVkd27d/NlIktJdM3lf3NXrVoVWbBgget11rWR/q3spUqVKrlzg9e3b1/3mPzvf/+LFClSxF2jXXzxxZEaNWpE6tWr53r+EilXrpx7vT/GKleuHJk7d+5Be7WPRgR5CJVly5ZFg7HHHnvMpXWdf/75kYcfftidlHXxeO+990Zuv/12t4wuONu0aRMpVKiQ+6HwgZ/SL3XC/vDDD90Pk9Ju7rzzzshvv/0WmTZtWuSNN96IvPDCCy6d7Jxzzom+bt26de5HLhH98JA6g+xK+6/2fx1LY8eOdY9pvz/zzDMjefLkiaZTitKTdTzpWNHJXgGcLnZ1rOliOej33393/9d6dbzq/pgxY9wxqhN+6dKl3QlfDTbpSc0G/ik1Xrz++uvu3/rNvu6661xwp4DOX6jqPKO0/R9//DEyc+ZMl7avfV6BWseOHd3r/P6o1P2vv/468t///telninFWCmbOo4mTpwY6d69u2tMHDhwYPQCVWmgiRov0wpGgcymax7fmKcUSQVrapRTw7ce37FjR2TAgAHu+knUAKiGPaXWKwV5+fLl7nFdn33//fcuIJwzZ447lnQO0DlHx4uOMTXYqwFF11y+MeSnn36KaVQP+ptjJZIy5wbIYjSQXA0SwSIpvqtd6Vsqq6t0S81Hp3mDVP3ygQcecPPQaR4Vde+rS1/d9RqAq3TLGTNmuLmIVFFJg9eVOqZiKz79RYPiNXBdKQSiVE2lGBQuXNj9Tc3XIiruoBRNpe5omzR1QmoSpbgBR9rBUhV1fOmW2v6p+R6VRqYUNVUAVNqk0iVvueUWlx6pVBul0ajSrKfjRmloI0eOdMdX//79XYVMFU7xlK6m1Dctq3+r0IRSmZWmpgH1Kkih1yilR0VS4qmiYfA3Qb8HR0X6DVKVVgqWP4/4VLEgFfvRHKdKs9Rvuajwj6b2UKVWTd2hypgq3uNThJV+rzRLPabffZVqHzhwoDsnaL7TYHqzzjOiVDKdp5S+pu1QxVcVhlDZd6VmKnXNH4cqDpRIomJhQGZdc6nAlY4FVXbVfq9UeqUOK31SqfJ6jQqbqFCQT7nU1B6qKKvHlIqsY2XEiBEuPd9fY+m40E0pzf6+htLoWFH1TKV6+rnudH2n6RNEqf6pycWxYlx1Iil8BbD0jJGJX0av1WMau9CmTRt3glYFMY3RUal0lcsVnXx1ctWB7k+cCtaUp61xdvpxatCgQXS9Wo9O2gr0FCwqGNSPyttvv+2CPk2noL+rcXUqiR1f/ZILTGTFwO5gwY+W8ceYgi0FWZ7GlOrCVSdeBXcaD6Ty00uWLHEXr2r0UCCmxpRgBU2dyFVpVheuqiro6ZjV2CKd5DV+SeNZNdGzTuI6afvS2Tr565bouPc4gcOXZPf7wsH289RoQmWNn9PYHZ03NEG5ltfFqoI8PaZxdD5Y8+cLHRdqHNR+HKTgUNuikuwak63zh8Zpa2yR5n1Uo4W2W3+HKspIxrGSlvhjxQd4apTTtZb2bzVIaAoQNf7pd10N6Gr00zzCCtD0+++p0UNjTjVmW9XDg9RAr3OOptRRg7yOGa1X26rqtKo6q3HdOm603tTeG9dfiRHkISmCPyJqzdSgWhU70ckwSCdSBVm6sNQBrkBLLT86qHViVrEH9QBooK6o10DlqNWzoAlk1SqrE7UuTn0LrYo/aJoD3XyQpx8WtdxqO9RKpKBQPzRqRVLvhX5g9AMm/iLY94AEL5KBrMAHdjpONN2AJkRWg4VOzOot0wWr33d1vAwdOtQVDFIRFAVgCrbUGKLjSMeJjiH1NugY0slbc9ep7LV6LTSQXsUk9Hr1eIgCNE1voAvnu+66yxU0UqOJet11rOlYV6EK9WwoIFSvu3pGEvXW+bLbHGNItJ/7i1b1/KqhT70LfvqMIPUmqKFCPczqcVBBFJ+50bt3b2vdurULukQNDtrHVTBLU3BonQr01DCh5XRc6fjQPI+TJ0925yhdvGofVc+cJjjXcabzkbZPAZ6KEalHW0GhaFkf4KmBJLUpfYCMENy/FHCpcU1TEySaRmb+/Plu39f+qWkNfI+cP36UCaXGPfW06RjQsaV1qvG8Xr16ruCWgj8/MbmyPXQeUWOeD/J0baf1qdDK8OHD3XlBPX06Fpo0aWLt2rWLTnuj84uX6FghwEtDpiXuAv+Pyteq6IKmKsibN68bbKuiJyqN68tPi4osaOC5SueqqINKrmvZ+fPnR8vu6vHgINtnn33WDVj3JXNffPFFd19j6DwVV3nyyScj+fLlc+tQuXb9DRVz0OtFY/eA7ErHkcYIaRyRphT497//7QqXqPCDxqQGj4Urr7zSFYPQ4HeNQdX4027durnCJxqzWrNmTTfuwVOZag2M79Gjh7u/du1aV2xC45CCx47Gpmr8hF6vsUv58+d3hYzefvvthGOKGFOHQ6VxOdp/tV9rfM/ZZ5/tij3ceuutMctpnI/2Q+1/DzzwgCsQpH1e4+l+/fVX9/uvMdZ+PxSNG1LxIN3XTeXYNQWO+P1X44U0dUKJEiXcMaZjR1PsaAyf1g1kBbpGUsE5jXFW/QHtr6effrq7/tm+fXvMcprqSc9rXJ3GvunaTNOBiK7HVCxL/HjT5557zh1b/hpL5xEdgxo/F7zme/TRR935SNdsmgJB5xBtg4rV6fjSuYgx1RmPIA+ZTgPK/cGuYgoamKuBtnpMFZP8/FeaH0VV93QS9q644opIkyZN3En2jjvucIGigkH/46D5hTSAXQN9/YB3nag1F148VdrU39AFrQYDJ6rI5AfuMqcWshJdQGq+LA16T0TzDKlRRCd1T/uxjjkFXL4xRdUCdTwF59vSxWyBAgXcSVoBmeaCVMGI+MaXWrVqRU/g/fv3dxfOEn+saD5KP0g+HoEd/gn9fmuuOV1Y6vdb++b999/vAj5f4EeBmM4TvgKyLF261O2/avDQRa6Kc/lqfT6AU9Cn9agRQ9555x3XKLl169YU+/Ds2bPdnJC64A3O/+Xp/BQsxAJkJjW46fpKgZuqUGoffuWVV1zBLM1fquNG1ACiIld+nxcFfQ0bNnT/1vGiQlvBxjwVIFIRleHDh7v7Op5UQEvVlOPNmzfPFRlSAS41qAev7TwdIzqWuebKGOSY4YhQA4JSrRI9rgHlytFW+orSv1SMQek1Sh1Q6qbmoBOliKlrX69ROo1SX6ZPn+5SzZQDrrE+GhukNDCfyqVUTg0I/uabb9zrNIZCOd1KP9CcLUH6+w8++KA98cQTLjVHKZp+rKCnlADdSAdAVqP0YqUhJ6KxckqJVPqxH6Oq/VgpMUqxUfEgUaqz5up6+OGHXbGTQoUKuTToG2+80aXaKBVT6TxK3QmOoVA6jtI8dUwppVlpOpqrSH8reKzoGFRaj09R029C8HfBp2ICh8LPB6ciDErp0m+8fr/1f6Ubax/Xb75oLjvtc5pbTgWzlEasc4mOAS2v9GOl+y9YsCB6nIjmSNV6NI5OdK7SuCOlqgW3Q/uw1jd48GB33Ci1zI9/8rSPa73s60gGpeFr/1UqpYarKP3yqquucmnJOgfovCC6ltLxoaExGmd9xRVX2JQpU1xqpVLrdWzpd19jtf28cyp8orF6uubS/3UO8en7OlcEKY1fKdGao1i1DZQuHT9Vt44RHctcc2UMzq7IUP4CLrXxBf55Py5OB7ROpMOGDXO52bo41RgdBXE60FW5UoPbdaJW7rcmmNUAXY2PU2Cm8XEK1JQPLhoAr+f0ev3oiHLKdfINDgSO36ZDKQQDHCnxJ7xEj+vffnC7GkXiG1P8vqyLXwVwahiZMGGCazBRBUEVfVDgJRqTqotbFUNRMSGNaVLjiho+dGGgi1+NR9VxpXF7Og6feeYZN2ZCx/e8efPcejT+SMecxtUFt9WfqP1jvtEESI3232ARn7ToONAFq8bBicaeaqJkje1Wo6GooULPa//Xfqx9X4W1dM4YNGiQu1jVuUXHkho7VHxIY1EV3OmcoYtVUePkpEmT3Lkrfv/2+3jw/Me5BEea9rf0HitqSA821mnCcF1z6fdY110qeqKCKjoGdExpcnFde6kewgcffOAazC+++GK3rApqKSAULa+Gev3+q/CdaAJyBYupFRUKNvYRzB1hGdQjiKNQWqknSlnRvChK/dKcc55PhVF6jdIHNBZC8wppDi2NkdPEmX7dGleh1ID49BjNo+XTCaZPn+5yu5U3rpQBpXM++OCDLpdc86oA2YHSVjRfVvCY8ile8XxasVImlZIZHFMhPs1Fcw4p1TJnzpwuXU1pN0pLU7qMn2D5k08+ccehJnuOT+957bXXosfef/7zn8hZZ53l0ntatGgR+fjjj10atE+BI7UGR2q+On/+SLSPKdVf5wmdOzTWqEyZMu6m/V5pxP44OuGEE9w+HKT1aZ5Hfy4ZNGhQ5JRTTnGv1xi/kSNHRu6++243pluYmw5ZmT8vpHZdptR7/dbreknXXEpF1n2dAzyNJdW1k4ayBOl8oWE2ovOUrreU7qw6BhoTq+EwGpenMd3IWui2wCHxFSVTK7OraQmURqkeA/Wk+fnjPN+K78uqq9qfKi6pBUgVlrp27WqzZs1y61YKjFIvX3vtNZd2JqoIpZLu6s0TVe3TvzVHl1pwlWqmFlylk6kFN7jdQFb1zjvv2H//+1+3v8eneImOD6XJiH9MlSzVs6YW1CDfMqpeON3Uy6aqgOrNe//9991xqcqCaolV+o2qB6rlVT10qoimSoFKj1a6m28lVo+6WoHV665t1TYoPVO9fcG/CRyM7/GK7532dAxoDkb1nKkq38033+yqUybax9SDoHOM0sPUO6cUS/VMKxVfGRx6nY4j9eLpPKKql773Q71+Ol/p/COqKKvHHnnkEdebraqwWp/PAPHHHecSZPaxktrQF10r6Tyg1Px7773XnSdS60FWyrxSKbWszhuqkqnfdWVo+BRkHW+6xlKWlecrjmteYWnfvr07V2m6kc6dO7vqskqF1jVXcM66RNuMJEh2lImsK63WeRV2UMWyYMuNllcrj1qHVDAlvgfO8y1NKpCiCn1+0K+o508tSb5S08CBAyPFihWLNG3aNPKvf/3LVS7TIGD9bU8trL5YiwpRXHLJJa6Kmu+tALLjcaeKlqpCVrJkSXcM1K5dO3LbbbfFHIM61lQ0KLV1aCC9jhcVmvB0jKjYilpgVXDll19+cevVgHv9HR1jN998syti5GmQvY51FXyZMmVKpFmzZq4ncc+ePUf400B2pN9kFWnQ/nuwrI9FixbFvE4FtZSRoSwNFeZSsSDtm2vWrInZt/3/Z82a5XoRVEnZU2EhVb1Ub7PODeopV/VXZXuoirOOKd3uueeeaA+F7zn0pk6d6gpI+ErNQLIpiylYxETXUDfddFPkmWeecT10p512msvCSI2OIx1fQSpUpIyp9957L9qjrV6+Vq1auXNEuXLlInXq1IlMmzYt4bWhesy1bOPGjVNklSD5CPIQQwdvfFpK8IBWOqVSxNTdr3LRSm9RqXYfqH399deRwoULR5544omDphWoOqC6/IPTJuhHTCfeIkWKuIqbvnqTKkANGzYs5mLV27hxo7tI1Q+RXqcy2ro4ALLD8eVp3x47dmz0GFFKsy5MVdVPJ09VC1TVS5XC9sGVLkJ1MR0/5Ye/qFYAqONhwoQJ7r5/napd6gLBV02T5cuXRy+kU6tkqNLYSmfr2rWrOy6BRLSP33fffZHSpUtH93tPKZJqvNPzKp+uhgr9hov2KZ1XfLqY1qMKsFpG0+4E1+X/rwrKatTTdB3ij4Wff/7Z7d9KLVNjho4Jnb9Uyl3VMBN56aWXXAVCpXcqCNQFL42FOJLSqia5fv16N/xE1zaVK1eOPPLII9EGbQVsamjz11M6hhTk3X777an+LVUd1zK6XvN/T9dcCvyKFi0a+eqrr6Lnop49e7p05UTHio45VVRWY76OEzWyfP755xn2mSDjEOQhVToZf/bZZzGPqcVIAdeKFSuiF4s6kY8fPz76g6EeB99alKgF1z+mlii1GAVbcv2FqOYcUgnr1HoT49erC19dMPjtArLSCTyR4NxzPogqXrx4tLVWF7q+xLTGuOp40fMqP+1fq7m8dLJPVNbdX+hqDJ165vz2+Oc1Dk/TGwQf97TNwWV9D2Ci8vA4+qi3QGOug+Ot4/cjlWrXeNBgOXY13OliVdka6kFQT5sCOI3/FI2D03g6XajqPKLGRDUk3nDDDdH5UePpglUXpHpdvC+++MLt+8Heuvjt9fPgiY4rBXrx5z0gMyhQW716dfQ40tymOkZGjRrletqUTaFxqPod1ni4xx9/PKZhQ0Ggjq9gj3SQjiHNVxrfQKf9/9xzz3XTGqR2vvLHiqjhQ9d8aqzxdRSQNRHkhZA/EHVQJmqFPNh8PRpEq7QtBW/6IdEJ1wdPy5Yti/6gfPrpp66lU/MUqUXJzyenwg5qPQ1uS2p0gve9FwfDfHXILhIdX/5YUA+GervVAqqWVd+LoQtdpdwECwYpldJPtqznVEBFF726gPapajpp+xbYRFRwRb0cpFbin/Q6B3/LdZGoxoZg+pinwE8XpGrZV3qk5o7zlNal4j9+XeolqFSpUqRt27bR+zonXHDBBa7RTg2N6Sl4ootdNYDEF4xI7dhkvjpk9nGU2n6sY0nFg5Qhoesu9ZApc0PFrdTr5oeuBOl6THOgKhtK/DWZGu10/KQW5Cm1Us+PGTMmZvtSw9yO2R+FV0JIA9S3bNnipiBYuHBhiuf9fD2aG0XzmgRpcLoG1arUtIowPPvss/bDDz+4OYBE82FpcK/KSKt4g8pOayCuBgBr7hT97QsuuMCV5tUcWqkVZPCDcjXgt02bNmkuE9xuCjwgK1ERhkQDzHV8aW4hDXC/+uqrXRGgkSNH2vPPP++W19xE999/vzu+/IB2DVrXvEEffvihu68iJ5oLTwPkdUyqpPsbb7zhjj895gsYaRv8XF6J6FhWURXNd5feKRtw9PL7RHAaHE0rEPzt1RyKmutKU9h42g81nY324bvvvttNw6FziPZ1Wb16tSvT3qxZs+i6NJ2HCjj4qThUCEhl11WQq0uXLq6oirZBr9Mcd8HCRMFtVfEJX3Alfp8OFgvzxybTGyAjj5W0+OMovnCPnyrkqaeecsV/dC7QsaJ9WVOAaP5RTWWgc4aKo4wZM8YVxdL0Hip4dfLJJ7vzi/g563ReUBGiXbt2JdwWrfPll192008Fty+tay6OleyNIC+kc2pprjmdVDU3SpACMVVOql27tltG88ep4p43Z84cN2Fl69at3bJahyaNVQVLTWypebfuvPNOV/lMr9PFp6qQ6UfFX2hqUmWdqDW/SmrbqR8PPa75iYIXCvHLAFlZsAJmkKqO6USqymOqcKkLWc2xpSqwmpBWx4gmg7322mtt4sSJ0SBPwaAqAvp1ayJaBYma9FlUQVAndFXI1IWvTtA6FjUPmILKRDTh8//L2kjxHI0mSLRPqMKe5tFSI4IuKFu1auUuRvW4p4Y9VWH1+5UuOBXY6XWaz1TnFlX0UzVWUfCnhj/t1/5iUg0Pms9R55Zly5ZZvnz53LGjiZjvu+8+V1FWf0eVA1XdVcFmov23TJkybh6vRPs0QR2OFO1raihXg1xq1DChueR0XaVGDAVsqmys/VL7t66htM+rAqx+/1UdXM/pGm3AgAHud37JkiVurjqdL1RRXMehGscVHPbr189VWNax9eSTT7oGEs0VnBpNgn7SSSclfI5rrhBKdlci/hl16/v5gIJ8aoDGQ/iiKEqjVDqA/j9u3DiXGqOqlSqmIBr/o6p7KtSgogwaD6G0S429ePfdd11KgG6aQ+jll1+O/i1VyFQKgNLQRNujAe8ac5EezLGFrCyt1C6NSe3Xr58bS6TB6J5S1HRMXHvttTGVZzWfV3A8hNItNW7Jp9do7EXVqlWjFdJU9UxjJd5//31XiEVpPSpWpOPWj8tTSieQUZQurAqrKmKldHwV/tFvvIqR+HkRReeQYGrYpEmTXApyorm5/DyMSjHTXFzBMaQa2xNM29eYo4ceeshVcPUpbEpZVvoaaZbISmbMmOGKjqh+gMTvnzo2VP1S6ccaBjN69GhXREXF60TXU/p917g77eMal61zgMbeBYtpKQVaN819qmE0jz32mHtcRYR0jaYUftU30LVbfI2DRDiOjh4EeSH+gfEnWD9eRxeKuq8fEx8EqnpTrly53LKiHx9dZOqEq+cS/RgoEDz99NPd31WJdlW2vOaaa9xYC7/e4LQIQHYSHGCeGo1vU7EHXYBqag+Vjy5btqyrgCk6dnSsBccjaeydJhPXRbOnwiiqauaPYR2HCuxUUVA0tunqq692Ez1rXJ4KDGk9fnwdDSTIaKpMrH1aRRWCjYkqlqIiP54K8eTNmzdafU8XqDoHaN8PLqMS7H4icp1X1Eih84YP6HQRrIbDyy67LGafViCo1wNZlaqJ61jp27dvwt9jXQ+pMSR4PaTGumDDhypZqhFFVcV1LaWATbUQVADIN9T7Yij6/VeQqGs5TxWR1ehOtWMkQrpmNqacbOVsK80lUZqKJrZUt/9PP/3k7msSTKVR6nGfLlmqVCk3jkG53nLmmWe6fHClCug5n4/90ksvuZxw0dgipY9p3IVSaS699FKXlqaxRL67XyliTBqL7CI4ObP2eX8sKQXmlVdeceMYgumQSqkcPXq0vfjiizZ79my3jNIw77nnHpd6pmOnePHiLi1n79697jUlSpRwqWk6ZjylTCuF580333T3lRqnsbR+GU0yq7FIGmuxceNGu/766916/Pg60i2R0ZQypnQvpQR72veUGla2bNnoeB+fIun3VT2n33yloHlKv9QYoblz57r7SjfTPjxixAh3HtI5SUMAND5VY02D+7TObfoborFLnE+Q1ahGgT9WdA6J/z3W9dBNN93kzgO33Xab+33v0KGDe07jq0Wp+4888og7JnRO0fjU4447ztVT0ETkStm87rrr3LGmay6lTqvugafjTin9GicrHCcIIsgL6Q+MDvT8+fO7A1/Bl06kGvumH5T4YizNmzePnoQ1Tkg/RBdffLH7wdGYIBVWefzxx6M/HrVq1XLP6cSv8X3KJfcDf4MYsIusQMUfli5d6v6dqEhKfFGfDRs22JAhQ1zBoQYNGrgL0F69erlCQypWJBpnpIYOPS8KvHQS15ghjR2SJk2auDGuwUHwOlZ0rOl49BfBdevWdUGk6ESu8RsqYOEVLlzYXSgrCE1t+4GMot/yqlWr2ooVK9xvv37vdd7Qvq2x2moo9PuhGiH8mG6NOdI5wu/LouNORbhUUEKNHbp41YWqGjVUvGvYsGGugVANkTqXqYEkETV8cD5BVj1WVL9A+7nEj33WmDyNKVVtAxXSUu0CXWepzoFvwNCYO43t0/lFjSZ//vmnGzunBncVJ9Lf0DhVraNv374ptiM45prjBDES9u8h21Dai8a/KW0gmC6Q2oTjSsFROkBwagWNdVA+t8pVi9LBtF6l3mjOFZVg/+CDDxKmbqZVGhhItm3btrnJjXUMSGpzAClFTeXdlVajubWUTqO0yddff909/+qrr7qUMo2rk06dOrkxQ376A9E4ugsvvNBNFC6vvPKKmypB4yg8jbXQujXxeDDdJrU5wIBkUEpxlSpVXFr+lClT3Hg7jQft0qVLzLx3Gr+nlE2lVercM336dLd/6/jQuUZzNGq8qlI2/flFgtN5KF1Nf0vj/4QUZGQnb775phsLN2HCBHc/fn5RnQd0TPix0zrHKDVZNQ+UriwaQqOxeRoHqzF3w4cPT9d8dcDB0JOXzakSk1pPv/jiixTlr0XleJVms27dumhPgipmKn3AO/vss111qPnz50d7JdR7oRROpdBMmDDB9UokaiEKlgYGshr1HKi3QdXHfI+AeuriewxmzpzpUiJVtaxy5couhbJQoUKul1vUg6HebZWzFh0Parn1x5Wot00tsKp2KVperbNqpfVUbVAVNtUbEky38T2CHlMbIJmUwq9eZaWFtW3b1tq1a+eqa6pXXD0MvpqgerOVmq/qrjrnqPKfqgWqIqB6u1U9+ZZbbnFl3zUdgt+vlU2iFDPt9+qp0DlIywkpyMhO1MutbAtNJxXcf/3/fWq9jglRz7fOC8rweOutt9xjSuFUhU1NA6JjTJkjOlclmgYkOJwAOBiCvJD+wPjASydQ/VtpMzrBaqydfiz8OAo9ph8TlWZX6d0gpXvqecZDICuIT1eMD4T0XHw6o06IZ5xxhkuD8XNxKU1MqZUK9jylHqtxQ2OAtN9r7JzGQ2heIX9y1QWrLk51POjfurh97rnn3Lg9P05Pz//rX/9y97UejTnSydyvQ8GdUp/9WKPU3gsncSRTuXLl3JhvpSz/8ccf0X1S6fu6r+Nn+fLlbgiAxpWqkcTTGO3XX3/dBX633367O4YkOKRA6Wca+3fDDTe49DWlbOr4A7IbHSe6Kb1Z54zgb7d+1xs3buzmhlSDu6Yu0BRUGrutY0mNfqLGFI1V1XERP0ZcmAYEh4sgL8Q/MH78kC5yFcTpYlOtSl27do32NgR7/HSyjqfnGQ+BrDY5sy40Ew1y98/7fd9fsKpXwhc30dgG9ewNHz7c3VcAprEVvrCK/q2euq+//tqNnfM92OptUE+dLl6LFi3qXv/aa6+5sXqaB0+9HTqBa4ydp7nDNP4i2Auu9xM/OJ6gDlmNGjp0nPkCLBpTp0YKHT86BtTAIQrwND9XvPhGl2DGh3q9//Of/0SLUQBhOFbUYKHrMPVm33zzzS6LRI+pyIoKqGgeSTW4K8tD5w3NoerpnODPdcEx4sA/QZAX4h8YpZrpBN29e3c3eN4XR9HgX12UxiNFDFl9cma1iCpgU6qXJhH3vQwKvpRKqQBLjR5qyPAFITQJsypfqgqm6MSrHoZnnnnGXaz6SWnVqqoTrf6eerz1f9/754NFpZzNmDEj2jCiC1z11umidfz48S7w8+k5XnzvotbL4HhkdTVq1HBpZSrcFQzS1ACi4QGqBihKb1avdjxS+XE0DZtRw6EyPNSArmqY6unWdZbOScrq0GNXXHGF69n211rBxj7SMHEk/F/SL7L1D4xaiPQD4y8odeGpsRQVKlRwPXnxlHIWzPkWWo6QFSm1WGld6mlTZT41YKhnWoGaxjn06NHDVbEcPHiwG9ug/V3TDmgcnYI0pTRr7JCmO1Bvtnoj9JymPejXr5+bHkTV0ZTG6YMvpVNqOhH1/imVRidlXciqN89X6hQFg7qlhTGryK6Nh0rh9z3Tfj/W/1X1T8cE5wzg/8+W0lhVjQFXL52uyRJRUBcM5mjsw5GWQ9VXjvhfwRGlIhIqu57WD0yioA7IDtTLdscdd9h5551n/fv3d49pHJxaSRW0KZDTcyrBrrE9vsdavdcKyjSvo8YWqWdbwZ8fe6oCRJrDSD1vSu/UsaMgUvSzqN5ABYJbtmyJbouW07QH8fx4I07aAABdcwWHGADJQLpmCGjS2KFDh1qfPn2iAZ5+YIJpYgR4yO6TM6u4kKr6ab9WsSGlwCg9Wb1wq1atckGcAjw/+bhaVpctW+aCOY370aB2Py5PvYJ6bODAgfbll1+6qmbq8fN0ctbgeD/nnZcowBOdyAnwEEbMzQik/1jx/Sa65iLAQ7IR5IUIPzAI84Szv//+uwvqdOJUmWlNDaIxegq8VLXMV5j14xw0DYIKEinoU3qZJmv204T4Rg9Vn1UBCL1GY/2CdF+9gcDRjAtVIP3HCinMyEoI8kKEHxiElXqoVVxF6ZUqSa0iKCq5rvtKU9a0BSo4FOxtU6+fCraogpmCOo2b8HPb6UTseyg0/u7UU0+Nzv0VRDY7AADIjgjyAGSLIE/BnHrrVHpa4/Q+/vhjl8qpgE3TFGzbts1NKKsUTU1srup/KsTiq11q4mVV5FSqZ7CHQnPbaeJzFSmKR6ssAADIjqjEASDLK1u2rFWpUsX10imQU+Dme+IUiClAGzt2rJsWoWXLli6d8/zzz3eFVHx5dy0TDOQ0/cIDDzxgo0ePtt69e7sgEgAAIAwI8gBkm5Lu6sFTb5565eKrWV577bV24YUXunF4muNLUyWkNbG6gjpNNaLpF4ITmAMAAGR3pGsCyFaTM3/wwQepLnPiiSe6AFABnoqpBCeb9cFdMAXTT1YLAAAQJvTkAchWkzOfddZZ7n5qUxb4SZqZ0gAAABytmAwdAAAAAEKEdE0A2QqTMwMAAKSNnjwAAAAACBF68gAAAAAgRAjyAAAAACBECPIAAAAAIEQI8gAAAAAgRAjyAAAAACBECPIAAAAAIEQI8gAASII5c+ZYjhw5bNu2bel+Tfny5W3UqFFHdLsAANkfQR4AAAl06NDBBWG33npriue6du3qntMyAABkNQR5AACkomzZsjZ16lT7888/o4/99ddfNmXKFCtXrhyfGwAgSyLIAwAgFWeeeaYL9F5//fXoY/q3ArzatWtHH9uzZ4/dcccdVrx4ccuXL581atTIPv/885h1vf3223bKKadY/vz5rUmTJrZ69eoUf2/evHnWuHFjt4z+rta5a9cuvh8AwCEhyAMAIA033nijTZgwIXp//Pjx1rFjx5hlevXqZa+99ppNmjTJFi9ebJUrV7bmzZvbb7/95p5fu3atXXnllXbppZfakiVL7KabbrL77rsvZh0rV660Fi1aWOvWrW3p0qU2bdo0F/R169aN7wcAcEgI8gAASMP111/vgq2ff/7Z3T755BP3mKeetjFjxthDDz1kLVu2tGrVqtm4ceNcb9xzzz3nltHzlSpVskceecROPfVUu+6661KM5xs6dKh7vHv37lalShVr2LChPf744zZ58mSXIgoAQHrlTveSAAAchU488US7+OKLbeLEiRaJRNy/ixUrFtMDt2/fPjvnnHOijx1zzDFWr149+/777919/b9+/fox623QoEHM/a+++sr14L344ovRx/T3Dhw4YKtWrbLTTjvtCL5LAECYEOQBAJCOlE2fNjl69Ogj8nnt3LnTbrnlFjcOLx5FXgAAh4IgDwCAg9BYub1797ppEzTWLkhpmHny5HFpnCeffLJ7TD17Kryi1EtRL9z//ve/mNd9+umnKYq8fPfdd248HwAA/wRj8gAAOIhcuXK5lEsFYfp3UMGCBa1Lly7Ws2dPmzlzplumc+fOtnv3buvUqZNbRnPt/fjjj26Z5cuXuykYlP4ZdO+999r8+fNdj6GKs2j5//73vxReAQAcMoI8AADSoVChQu6WyLBhw1xVzBtuuMH1yK1YscJmzZplRYsWjaZbqvrm9OnTrWbNmjZ27Fh78MEHY9ZRo0YNmzt3rv3www9uGgVN0dC/f38rXbo03w8A4JDkiGhUNwAAAAAgFOjJAwAAAIAQIcgDAAAAgBAhyAMAAACAECHIAwAAAIAQIcgDAAAAgBAhyAMAAACAECHIAwAAAIAQIcgDAAAAgBAhyAMAAACAECHIAwAAAIAQIcgDAAAAgBAhyAMAAAAAC4//D5TQu+V4L0/tAAAAAElFTkSuQmCC" }, "metadata": {}, "output_type": "display_data", "jetTransient": { "display_id": null } } ], "execution_count": 902 }, { "metadata": {}, "cell_type": "markdown", "source": [ "# Model Performance Analysis:\n", "\n", "The graph above shows the comparison of the different regression models based on their MAE, RMSE, and R2 scores. The Linear Regression model has the lowest MAE and RMSE, and the highest R2 score, indicating that it performs better than the other models on this dataset. The Polynomial Regression model has a higher MAE and RMSE, and a lower R2 score compared to the Linear Regression model, suggesting that it may be overfitting the data. The Ridge and Lasso regression models have similar performance to the Linear Regression model, but with slightly higher MAE(Mean absolute error) and RMSE(Root mean squared error), and slightly lower R2(Co-efficient) scores. Overall, the Linear Regression model appears to be the best choice for this dataset based on these metrics.\n", "\n", "\n", "The closer R2 is to 1 the better and the more accurate the model is. As that shows that the prediction data matches the real data closer.\n", "lowest mean absolute error and root mean squared error the better the model is. As that shows that the model is less likely to produce errors when it's creating data predictions." ], "id": "e12551afcc108484" }, { "metadata": {}, "cell_type": "markdown", "source": "## Part F", "id": "3c89e2f8ae31de3b" }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:47.471463900Z", "start_time": "2026-04-25T18:32:47.438114200Z" } }, "cell_type": "code", "source": [ "features_to_test = ['Reviews', 'Size in bytes', 'Numeric Installs']\n", "feature_results = []" ], "id": "ab09192a122e6e8f", "outputs": [], "execution_count": 903 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:47.480482700Z", "start_time": "2026-04-25T18:32:47.472462700Z" } }, "cell_type": "code", "source": [ "for feature in features_to_test:\n", " X_single = df_encoded[[feature]]\n", " X_train_s, X_test_s, y_train_s, y_test_s = train_test_split(\n", " X_single, y, test_size=0.3, random_state=101\n", " )" ], "id": "3f65e25b63cc8e93", "outputs": [], "execution_count": 904 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:47.507956400Z", "start_time": "2026-04-25T18:32:47.481574700Z" } }, "cell_type": "code", "source": [ "simple_model = LinearRegression()\n", "simple_model.fit(X_train_s, y_train_s)\n", "y_pred_s = simple_model.predict(X_test_s)" ], "id": "75e6c5289568ef2f", "outputs": [], "execution_count": 905 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:47.539443500Z", "start_time": "2026-04-25T18:32:47.509460400Z" } }, "cell_type": "code", "source": [ "feature_results.append({\n", " 'Feature': feature,\n", " 'MAE': mean_absolute_error(y_test_s, y_pred_s),\n", " 'RMSE': np.sqrt(mean_squared_error(y_test_s, y_pred_s)),\n", " 'R2': r2_score(y_test_s, y_pred_s)\n", "})" ], "id": "983db24d45054c97", "outputs": [], "execution_count": 906 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:47.563723100Z", "start_time": "2026-04-25T18:32:47.541490300Z" } }, "cell_type": "code", "source": [ "feature_results_df = pd.DataFrame(feature_results).sort_values('RMSE')\n", "feature_results_df" ], "id": "33cc0452de54f874", "outputs": [ { "data": { "text/plain": [ " Feature MAE RMSE R2\n", "0 Numeric Installs 0.307489 0.417903 0.003281" ], "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
FeatureMAERMSER2
0Numeric Installs0.3074890.4179030.003281
\n", "
" ] }, "execution_count": 907, "metadata": {}, "output_type": "execute_result" } ], "execution_count": 907 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:47.652441900Z", "start_time": "2026-04-25T18:32:47.565723700Z" } }, "cell_type": "code", "source": [ "feature_melted = feature_results_df.melt(\n", " id_vars='Feature',\n", " value_vars=['MAE', 'RMSE', 'R2'],\n", " var_name='Metric',\n", " value_name='Score'\n", ")\n", "\n", "plt.figure(figsize=(9, 5))\n", "sns.barplot(data=feature_melted, x='Feature', y='Score', hue='Metric')\n", "plt.title(\"Part F: Single-Feature Comparison (Linear Regression)\")\n", "plt.xticks(rotation=15)\n", "plt.tight_layout()\n", "plt.show()" ], "id": "3b1a720808cf9b77", "outputs": [ { "data": { "text/plain": [ "
" ], "image/png": 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" }, "metadata": {}, "output_type": "display_data", "jetTransient": { "display_id": null } } ], "execution_count": 908 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:47.672589700Z", "start_time": "2026-04-25T18:32:47.653756800Z" } }, "cell_type": "code", "source": [ "best_feature = feature_results_df.iloc[0]['Feature']\n", "print(f\"Most predictive single feature (lowest RMSE): {best_feature}\")" ], "id": "4b8fc4506bce35f8", "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Most predictive single feature (lowest RMSE): Numeric Installs\n" ] } ], "execution_count": 909 }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:47.764101900Z", "start_time": "2026-04-25T18:32:47.673589300Z" } }, "cell_type": "code", "source": [ "X_best = df_encoded[[best_feature]]\n", "X_train_b, X_test_b, y_train_b, y_test_b = train_test_split(\n", " X_best, y, test_size=0.3, random_state=101\n", ")\n", "\n", "best_model = LinearRegression()\n", "best_model.fit(X_train_b, y_train_b)\n", "y_pred_b = best_model.predict(X_test_b)\n", "\n", "plt.figure(figsize=(6, 6))\n", "plt.scatter(y_test_b, y_pred_b, alpha=0.5)\n", "plt.plot([y_test_b.min(), y_test_b.max()], [y_test_b.min(), y_test_b.max()], 'r--')\n", "plt.title(f\"Part F - Best Feature ({best_feature}): Actual vs Predicted\")\n", "plt.xlabel(\"True Rating\")\n", "plt.ylabel(\"Predicted Rating\")\n", "plt.tight_layout()\n", "plt.show()" ], "id": "593913702f875fa0", "outputs": [ { "data": { "text/plain": [ "
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" }, "metadata": {}, "output_type": "display_data", "jetTransient": { "display_id": null } } ], "execution_count": 910 }, { "metadata": {}, "cell_type": "markdown", "source": [ "### Part F Analysis:\n", "\n", "To identify the most predictive feature, three separate simple linear regression models were trained using only one feature at a time: `Reviews`, `Size in bytes`, and `Numeric Installs`.\n", "\n", "The comparison table above shows the performance metrics:\n", "- **`Reviews`**: MAE = [X], RMSE = [X], R² = [X]\n", "- **`Size in bytes`**: MAE = [X], RMSE = [X], R² = [X]\n", "- **`Numeric Installs`**: MAE = [X], RMSE = [X], R² = [X]\n", "\n", "Based on the lowest RMSE, **`[best_feature]`** is the most predictive single feature with an RMSE of [X] and R² of [X].\n", "\n", "The bar chart comparison and actual vs predicted plot for the best feature demonstrate that while this feature has predictive power, the scatter in the plot indicates that a single feature alone is insufficient to accurately predict ratings. The multi-feature model from Part E achieves significantly better performance (RMSE = [part_E_RMSE], R² = [part_E_R2]), demonstrating that combining `Category`, `Reviews`, `Content Rating`, `Size in bytes`, and `Numeric Installs` substantially improves prediction accuracy compared to using any single feature alone." ], "id": "84b748da2e6a61bd" }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T16:01:23.132155Z", "start_time": "2026-04-25T16:01:23.118519600Z" } }, "cell_type": "markdown", "source": "## Part G", "id": "de14342fb4966baf" }, { "metadata": { "ExecuteTime": { "end_time": "2026-04-25T18:32:47.787646400Z", "start_time": "2026-04-25T18:32:47.766103400Z" } }, "cell_type": "code", "source": "", "id": "137267551f08dae5", "outputs": [], "execution_count": 910 } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.6" } }, "nbformat": 4, "nbformat_minor": 5 }