From 33a9d08451336dd59956695e57b59f052d05530a Mon Sep 17 00:00:00 2001 From: "a.puchkina" Date: Sat, 9 Nov 2024 12:13:01 +0400 Subject: [PATCH] =?UTF-8?q?=D0=B2=D1=81=D0=B5=20=D0=BE=D0=BA=D0=B5=D0=B9?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- lab_3/lab3.ipynb | 269 ++++++++++++++++++++++++----------------------- 1 file changed, 137 insertions(+), 132 deletions(-) diff --git a/lab_3/lab3.ipynb b/lab_3/lab3.ipynb index 665e5d5..27b21b3 100644 --- a/lab_3/lab3.ipynb +++ b/lab_3/lab3.ipynb @@ -16,7 +16,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -55,7 +55,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -89,7 +89,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -312,7 +312,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -527,7 +527,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -562,7 +562,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -589,6 +589,9 @@ "df['Ram'] = df['Ram'].apply(lambda x: int(re.search(r'\\d+', x).group()) if re.search(r'\\d+', x) else None)\n", "df['Camera'] = df['Camera'].apply(lambda x: int(re.search(r'\\d+', x).group()) if re.search(r'\\d+', x) else None)\n", "\n", + "# Удаление запятых из столбца Price и преобразование в числовой формат\n", + "df['Price'] = df['Price'].str.replace(',', '').astype(float)\n", + "\n", "# Разделение на обучающую и тестовую выборки (например, 70% обучающая, 30% тестовая)\n", "train_df, test_df = train_test_split(df, test_size=0.3, random_state=42)\n", "\n", @@ -642,7 +645,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -670,6 +673,9 @@ "df['Camera'] = pd.to_numeric(df['Camera'], errors='coerce')\n", "df['Display'] = pd.to_numeric(df['Display'], errors='coerce')\n", "\n", + "# Удаление запятых из столбца Price и преобразование в числовой формат\n", + "df['Price'] = df['Price'].str.replace(',', '').astype(float)\n", + "\n", "# Разделение на обучающую и тестовую выборки (например, 70% обучающая, 30% тестовая)\n", "train_df, test_df = train_test_split(df, test_size=0.3, random_state=42)\n", "\n", @@ -709,7 +715,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -751,6 +757,9 @@ "df['Camera'] = pd.to_numeric(df['Camera'], errors='coerce')\n", "df['Display'] = pd.to_numeric(df['Display'], errors='coerce')\n", "\n", + "# Удаление запятых из столбца Price и преобразование в числовой формат\n", + "df['Price'] = df['Price'].str.replace(',', '').astype(float)\n", + "\n", "# Разделение на обучающую и тестовую выборки (например, 70% обучающая, 30% тестовая)\n", "train_df, test_df = train_test_split(df, test_size=0.3, random_state=42)\n", "\n", @@ -809,103 +818,9 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 13, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Обучающая выборка после конструирования признаков:\n", - " Unnamed: 0 Rating Spec_score No_of_sim Ram \\\n", - "id \n", - "0 305 4.70 86 Dual Sim, 3G, 4G, 5G, VoLTE, 12 GB RAM \n", - "1 941 4.45 71 Dual Sim, 3G, 4G, VoLTE, 4 GB RAM \n", - "2 800 4.20 68 Dual Sim, 3G, 4G, VoLTE, 4 GB RAM \n", - "3 97 4.25 69 Dual Sim, 3G, 4G, VoLTE, 4 GB RAM \n", - "4 1339 4.30 74 Dual Sim, 3G, 4G, VoLTE, 6 GB RAM \n", - "\n", - " Battery External_Memory Android_version company \\\n", - "id \n", - "0 5000 Android v12 NaN Realme \n", - "1 5000 Memory Card Supported, upto 1 TB 12 Motorola \n", - "2 5000 Memory Card Supported 12 Vivo \n", - "3 5000 Memory Card Supported 12 Vivo \n", - "4 5000 Memory Card Supported, upto 256 GB 12 Lava \n", - "\n", - " Inbuilt_memory fast_charging \\\n", - "id \n", - "0 256 GB inbuilt 65W Fast Charging \n", - "1 64 GB inbuilt 10W Fast Charging \n", - "2 64 GB inbuilt 10W Fast Charging \n", - "3 128 GB inbuilt 10W Fast Charging \n", - "4 128 GB inbuilt NaN \n", - "\n", - " Screen_resolution Processor \n", - "id \n", - "0 1080 x 2400 px Octa Core \n", - "1 720 x 1600 px Octa Core \n", - "2 720 x 1600 px Display with Water Drop Notch Octa Core \n", - "3 720 x 1600 px Display with Water Drop Notch Octa Core \n", - "4 1600 x 720 px Octa Core \n", - "Контрольная выборка после конструирования признаков:\n", - " Unnamed: 0 Rating Spec_score No_of_sim Ram \\\n", - "id \n", - "1028 NaN NaN NaN \n", - "825 NaN NaN NaN \n", - "900 NaN NaN NaN \n", - "702 NaN NaN NaN \n", - "230 1050 4.05 90 Dual Sim, 3G, 4G, 5G, VoLTE, 8 GB RAM \n", - "\n", - " Battery External_Memory Android_version company Inbuilt_memory \\\n", - "id \n", - "1028 NaN NaN NaN NaN \n", - "825 NaN NaN NaN NaN \n", - "900 NaN NaN NaN NaN \n", - "702 NaN NaN NaN NaN \n", - "230 4500 Android v12 NaN Motorola 128 GB inbuilt \n", - "\n", - " fast_charging Screen_resolution Processor \n", - "id \n", - "1028 NaN NaN NaN \n", - "825 NaN NaN NaN \n", - "900 NaN NaN NaN \n", - "702 NaN NaN NaN \n", - "230 125W Fast Charging 1080 x 2400 px Octa Core \n", - "Тестовая выборка после конструирования признаков:\n", - " Unnamed: 0 Rating Spec_score No_of_sim \\\n", - "id \n", - "427 187 4.40 91 Dual Sim, 3G, 4G, 5G, VoLTE, \n", - "1088 NaN NaN \n", - "668 592 4.45 91 Dual Sim, 3G, 4G, 5G, VoLTE, \n", - "572 1130 4.60 75 Dual Sim, 3G, 4G, VoLTE, \n", - "115 117 4.60 72 Dual Sim, 3G, 4G, VoLTE, \n", - "\n", - " Ram Battery External_Memory Android_version \\\n", - "id \n", - "427 12 GB RAM 5000 Memory Card Not Supported 14 \n", - "1088 NaN NaN NaN \n", - "668 12 GB RAM 4500 Android v12 NaN \n", - "572 6 GB RAM 5000 Memory Card Supported, upto 1 TB 13 \n", - "115 4 GB RAM 5000 Memory Card Supported, upto 1 TB 12 \n", - "\n", - " company Inbuilt_memory fast_charging \\\n", - "id \n", - "427 Vivo 256 GB inbuilt 120W Fast Charging \n", - "1088 NaN NaN NaN \n", - "668 Honor 256 GB inbuilt 100W Fast Charging \n", - "572 Xiaomi 128 GB inbuilt 18W Fast Charging \n", - "115 Vivo 64 GB inbuilt 18W Fast Charging \n", - "\n", - " Screen_resolution Processor \n", - "id \n", - "427 1260 x 2800 px Octa Core \n", - "1088 NaN NaN \n", - "668 1200 x 2652 px Octa Core \n", - "572 720 x 1600 px Octa Core \n", - "115 720 x 1612 px Display with Water Drop Notch Octa Core \n" - ] - }, { "name": "stderr", "output_type": "stream", @@ -956,10 +871,6 @@ " pd.to_datetime(\n", "d:\\ULSTU\\AIM2\\AIM-PIbd-32-Puchkina-A-A\\aimenv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n", " pd.to_datetime(\n", - "d:\\ULSTU\\AIM2\\AIM-PIbd-32-Puchkina-A-A\\aimenv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n", - " pd.to_datetime(\n", - "d:\\ULSTU\\AIM2\\AIM-PIbd-32-Puchkina-A-A\\aimenv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n", - " pd.to_datetime(\n", "d:\\ULSTU\\AIM2\\AIM-PIbd-32-Puchkina-A-A\\aimenv\\Lib\\site-packages\\featuretools\\synthesis\\deep_feature_synthesis.py:169: UserWarning: Only one dataframe in entityset, changing max_depth to 1 since deeper features cannot be created\n", " warnings.warn(\n", "d:\\ULSTU\\AIM2\\AIM-PIbd-32-Puchkina-A-A\\aimenv\\Lib\\site-packages\\featuretools\\computational_backends\\feature_set_calculator.py:143: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n", @@ -999,7 +910,107 @@ "d:\\ULSTU\\AIM2\\AIM-PIbd-32-Puchkina-A-A\\aimenv\\Lib\\site-packages\\featuretools\\computational_backends\\feature_set_calculator.py:143: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n", " df = pd.concat([df, default_df], sort=True)\n", "d:\\ULSTU\\AIM2\\AIM-PIbd-32-Puchkina-A-A\\aimenv\\Lib\\site-packages\\featuretools\\computational_backends\\feature_set_calculator.py:143: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n", - " df = pd.concat([df, default_df], sort=True)\n", + " df = pd.concat([df, default_df], sort=True)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Обучающая выборка после конструирования признаков:\n", + " Unnamed: 0 Rating Spec_score No_of_sim Ram \\\n", + "id \n", + "0 305 4.70 86 Dual Sim, 3G, 4G, 5G, VoLTE, 12 GB RAM \n", + "1 941 4.45 71 Dual Sim, 3G, 4G, VoLTE, 4 GB RAM \n", + "2 800 4.20 68 Dual Sim, 3G, 4G, VoLTE, 4 GB RAM \n", + "3 97 4.25 69 Dual Sim, 3G, 4G, VoLTE, 4 GB RAM \n", + "4 1339 4.30 74 Dual Sim, 3G, 4G, VoLTE, 6 GB RAM \n", + "\n", + " Battery External_Memory Android_version Price \\\n", + "id \n", + "0 5000 Android v12 NaN 30999.0 \n", + "1 5000 Memory Card Supported, upto 1 TB 12 6999.0 \n", + "2 5000 Memory Card Supported 12 8999.0 \n", + "3 5000 Memory Card Supported 12 9999.0 \n", + "4 5000 Memory Card Supported, upto 256 GB 12 8499.0 \n", + "\n", + " company Inbuilt_memory fast_charging \\\n", + "id \n", + "0 Realme 256 GB inbuilt 65W Fast Charging \n", + "1 Motorola 64 GB inbuilt 10W Fast Charging \n", + "2 Vivo 64 GB inbuilt 10W Fast Charging \n", + "3 Vivo 128 GB inbuilt 10W Fast Charging \n", + "4 Lava 128 GB inbuilt NaN \n", + "\n", + " Screen_resolution Processor \n", + "id \n", + "0 1080 x 2400 px Octa Core \n", + "1 720 x 1600 px Octa Core \n", + "2 720 x 1600 px Display with Water Drop Notch Octa Core \n", + "3 720 x 1600 px Display with Water Drop Notch Octa Core \n", + "4 1600 x 720 px Octa Core \n", + "Контрольная выборка после конструирования признаков:\n", + " Unnamed: 0 Rating Spec_score No_of_sim Ram \\\n", + "id \n", + "1028 NaN NaN NaN \n", + "825 NaN NaN NaN \n", + "900 NaN NaN NaN \n", + "702 NaN NaN NaN \n", + "230 1050 4.05 90 Dual Sim, 3G, 4G, 5G, VoLTE, 8 GB RAM \n", + "\n", + " Battery External_Memory Android_version Price company \\\n", + "id \n", + "1028 NaN NaN NaN NaN \n", + "825 NaN NaN NaN NaN \n", + "900 NaN NaN NaN NaN \n", + "702 NaN NaN NaN NaN \n", + "230 4500 Android v12 NaN 62990.0 Motorola \n", + "\n", + " Inbuilt_memory fast_charging Screen_resolution Processor \n", + "id \n", + "1028 NaN NaN NaN NaN \n", + "825 NaN NaN NaN NaN \n", + "900 NaN NaN NaN NaN \n", + "702 NaN NaN NaN NaN \n", + "230 128 GB inbuilt 125W Fast Charging 1080 x 2400 px Octa Core \n", + "Тестовая выборка после конструирования признаков:\n", + " Unnamed: 0 Rating Spec_score No_of_sim \\\n", + "id \n", + "427 187 4.40 91 Dual Sim, 3G, 4G, 5G, VoLTE, \n", + "1088 NaN NaN \n", + "668 592 4.45 91 Dual Sim, 3G, 4G, 5G, VoLTE, \n", + "572 1130 4.60 75 Dual Sim, 3G, 4G, VoLTE, \n", + "115 117 4.60 72 Dual Sim, 3G, 4G, VoLTE, \n", + "\n", + " Ram Battery External_Memory Android_version \\\n", + "id \n", + "427 12 GB RAM 5000 Memory Card Not Supported 14 \n", + "1088 NaN NaN NaN \n", + "668 12 GB RAM 4500 Android v12 NaN \n", + "572 6 GB RAM 5000 Memory Card Supported, upto 1 TB 13 \n", + "115 4 GB RAM 5000 Memory Card Supported, upto 1 TB 12 \n", + "\n", + " Price company Inbuilt_memory fast_charging \\\n", + "id \n", + "427 63999.0 Vivo 256 GB inbuilt 120W Fast Charging \n", + "1088 NaN NaN NaN NaN \n", + "668 54990.0 Honor 256 GB inbuilt 100W Fast Charging \n", + "572 8499.0 Xiaomi 128 GB inbuilt 18W Fast Charging \n", + "115 11580.0 Vivo 64 GB inbuilt 18W Fast Charging \n", + "\n", + " Screen_resolution Processor \n", + "id \n", + "427 1260 x 2800 px Octa Core \n", + "1088 NaN NaN \n", + "668 1200 x 2652 px Octa Core \n", + "572 720 x 1600 px Octa Core \n", + "115 720 x 1612 px Display with Water Drop Notch Octa Core \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ "d:\\ULSTU\\AIM2\\AIM-PIbd-32-Puchkina-A-A\\aimenv\\Lib\\site-packages\\woodwork\\logical_types.py:841: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", " series = series.replace(ww.config.get_option(\"nan_values\"), np.nan)\n" ] @@ -1021,6 +1032,9 @@ "df['Camera'] = pd.to_numeric(df['Camera'], errors='coerce')\n", "df['Display'] = pd.to_numeric(df['Display'], errors='coerce')\n", "\n", + "# Удаление запятых из столбца Price и преобразование в числовой формат\n", + "df['Price'] = df['Price'].str.replace(',', '').astype(float)\n", + "\n", "# Разделение на обучающую и тестовую выборки (например, 70% обучающая, 30% тестовая)\n", "train_df, test_df = train_test_split(df, test_size=0.3, random_state=42)\n", "\n", @@ -1073,18 +1087,9 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 14, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Размер обучающей выборки: 671\n", - "Размер контрольной выборки: 288\n", - "Размер тестовой выборки: 411\n" - ] - }, { "name": "stderr", "output_type": "stream", @@ -1099,6 +1104,9 @@ "name": "stdout", "output_type": "stream", "text": [ + "Размер обучающей выборки: 671\n", + "Размер контрольной выборки: 288\n", + "Размер тестовой выборки: 411\n", "Feature Importance:\n", " feature importance\n", "4 Price 0.999443\n", @@ -1195,18 +1203,16 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Размер обучающей выборки: 66\n", - "Размер контрольной выборки: 29\n", - "Размер тестовой выборки: 42\n", - "Mean Squared Error: 13048795.366100002\n", - "R2 Score: -0.23881710583662308\n" + "Размер обучающей выборки: 671\n", + "Размер контрольной выборки: 288\n", + "Размер тестовой выборки: 411\n" ] }, { @@ -1229,12 +1235,14 @@ "name": "stdout", "output_type": "stream", "text": [ - "Cross-validated Mean Squared Error: 394482934.1724652\n" + "Mean Squared Error: 53834536.21488374\n", + "R2 Score: 0.9445638071244045\n", + "Cross-validated Mean Squared Error: 311290473.964474\n" ] }, { "data": { - "image/png": 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", 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", 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" ] @@ -1246,13 +1254,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "Train Mean Squared Error: 46662951.69621668\n", - "Train R2 Score: 0.9411587287387594\n" + "Train Mean Squared Error: 40281623.425488226\n", + "Train R2 Score: 0.9581963040734582\n" ] }, { "data": { - "image/png": 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", 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", 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" ] @@ -1275,9 +1283,6 @@ "# Загрузка данных\n", "df = pd.read_csv(\"..//static//csv//mobile phone price prediction.csv\")\n", "\n", - "# Уменьшение размера выборки для ускорения работы (опционально)\n", - "df = df.sample(frac=0.1, random_state=42)\n", - "\n", "# Преобразование столбца Battery в числовой формат\n", "df['Battery'] = df['Battery'].apply(lambda x: int(re.search(r'\\d+', x).group()) if re.search(r'\\d+', x) else None)\n", "\n",