\\n\",\n \" \\n\",\n \" \\n\",\n \" \"\n ]\n },\n \"metadata\": {},\n \"execution_count\": 210\n }\n ]\n },\n {\n \"cell_type\": \"code\",\n \"source\": [\n \"data_test\"\n ],\n \"metadata\": {\n \"colab\": {\n \"base_uri\": \"https://localhost:8080/\",\n \"height\": 488\n },\n \"id\": \"Q5hdW9sfFjcq\",\n \"outputId\": \"820a21e2-3ab4-4003-efbb-fe91710f4f1c\"\n },\n \"execution_count\": 211,\n \"outputs\": [\n {\n \"output_type\": \"execute_result\",\n \"data\": {\n \"text/plain\": [\n \" ID MSSubClass LotArea Street HouseStyle ExterQual BldgType LotConfig \\\\\\n\",\n \"0 1 70 13728 Pave 2Story TA 1Fam Corner \\n\",\n \"1 2 60 35760 Pave 2Story Gd 1Fam CulDSac \\n\",\n \"2 3 80 9880 Pave SLvl TA 1Fam Inside \\n\",\n \"3 4 20 9120 Pave 1Story TA 1Fam Inside \\n\",\n \"4 5 160 4017 Pave 2Story Gd TwnhsE Inside \\n\",\n \".. ... ... ... ... ... ... ... ... \\n\",\n \"287 288 60 7917 Pave 2Story TA 1Fam Inside \\n\",\n \"288 289 20 13175 Pave 1Story TA 1Fam Inside \\n\",\n \"289 290 70 9042 Pave 2Story Ex 1Fam Inside \\n\",\n \"290 291 20 9717 Pave 1Story TA 1Fam Inside \\n\",\n \"291 292 20 9937 Pave 1Story Gd 1Fam Inside \\n\",\n \"\\n\",\n \" OverallQual OverallCond ... WoodDeckSF OpenPorchSF EnclosedPorch \\\\\\n\",\n \"0 6 7 ... 0 0 0 \\n\",\n \"1 10 5 ... 361 76 0 \\n\",\n \"2 Missing 6 ... 203 0 0 \\n\",\n \"3 6 6 ... 0 0 0 \\n\",\n \"4 7 5 ... 0 54 0 \\n\",\n \".. ... ... ... ... ... ... \\n\",\n \"287 6 5 ... 0 40 0 \\n\",\n \"288 6 6 ... 349 0 0 \\n\",\n \"289 7 9 ... 0 60 0 \\n\",\n \"290 5 6 ... 366 0 112 \\n\",\n \"291 5 6 ... 736 68 0 \\n\",\n \"\\n\",\n \" 3SsnPorch ScreenPorch PoolArea MiscVal MoSold YrSold SalePrice \\n\",\n \"0 0 90 0 0 7 2008 235000 \\n\",\n \"1 0 0 0 0 7 2006 625000 \\n\",\n \"2 0 0 576 0 7 2008 171000 \\n\",\n \"3 0 288 0 1400 11 2008 163000 \\n\",\n \"4 0 0 0 0 3 2008 171900 \\n\",\n \".. ... ... ... ... ... ... ... \\n\",\n \"287 0 0 0 0 8 2007 175000 \\n\",\n \"288 0 0 0 0 2 2010 210000 \\n\",\n \"289 0 0 0 2500 5 2010 266500 \\n\",\n \"290 0 0 0 0 4 2010 142125 \\n\",\n \"291 0 0 0 0 6 2008 147500 \\n\",\n \"\\n\",\n \"[292 rows x 40 columns]\"\n ],\n \"text/html\": [\n \"\\n\",\n \"
\\n\",\n \"
\\n\",\n \"
\\n\",\n \"\\n\",\n \"\\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \"
IDMSSubClassLotAreaStreetHouseStyleExterQualBldgTypeLotConfigOverallQualOverallCond...WoodDeckSFOpenPorchSFEnclosedPorch3SsnPorchScreenPorchPoolAreaMiscValMoSoldYrSoldSalePrice
017013728Pave2StoryTA1FamCorner67...0000900072008235000
126035760Pave2StoryGd1FamCulDSac105...361760000072006625000
23809880PaveSLvlTA1FamInsideMissing6...2030000576072008171000
34209120Pave1StoryTA1FamInside66...000028801400112008163000
451604017Pave2StoryGdTwnhsEInside75...0540000032008171900
..................................................................
287288607917Pave2StoryTA1FamInside65...0400000082007175000
2882892013175Pave1StoryTA1FamInside66...34900000022010210000
289290709042Pave2StoryEx1FamInside79...0600000250052010266500
290291209717Pave1StoryTA1FamInside56...3660112000042010142125
291292209937Pave1StoryGd1FamInside56...736680000062008147500
\\n\",\n \"

292 rows × 40 columns

\\n\",\n \"
\\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \"\\n\",\n \" \\n\",\n \"
\\n\",\n \"
\\n\",\n \" \"\n ]\n },\n \"metadata\": {},\n \"execution_count\": 211\n }\n ]\n },\n {\n \"cell_type\": \"code\",\n \"source\": [\n \"# replace the missing values OverallQual, OverallCond, YearBuilt with the mean\\n\",\n \"\\n\",\n \"def replace_Missing(data):\\n\",\n \" # first we replace all the missing values with NaN or null\\n\",\n \" data = data.replace('Missing',np.nan)\\n\",\n \"\\n\",\n \" # converting the columns to numeric type as some elements are of string type\\n\",\n \" data[\\\"OverallQual\\\"] = pd.to_numeric(data[\\\"OverallQual\\\"])\\n\",\n \" data[\\\"OverallCond\\\"] = pd.to_numeric(data[\\\"OverallCond\\\"])\\n\",\n \" data[\\\"YearBuilt\\\"] = pd.to_numeric(data[\\\"YearBuilt\\\"])\\n\",\n \"\\n\",\n \" # replacing the Nan or \\\"Missing\\\" positions with the mean value of that column\\n\",\n \" data['OverallQual'] = data['OverallQual'].fillna(data['OverallQual'].mean())\\n\",\n \" data['OverallCond'] = data['OverallCond'].fillna(data['OverallCond'].mean())\\n\",\n \" data['YearBuilt'] = data['YearBuilt'].fillna(data['YearBuilt'].mean())\\n\",\n \"\\n\",\n \" return data\\n\",\n \"\\n\",\n \"# Calling the function to remove the missing values from train and test data\\n\",\n \"data_train = replace_Missing(data_train)\\n\",\n \"data_test = replace_Missing(data_test)\\n\",\n \"\\n\",\n \"data_train\"\n ],\n \"metadata\": {\n \"colab\": {\n \"base_uri\": \"https://localhost:8080/\",\n \"height\": 488\n },\n \"id\": \"MGE7g_QS1PEP\",\n \"outputId\": \"0d93909b-7cc4-40b1-c845-fc6f17ca117d\"\n },\n \"execution_count\": 212,\n \"outputs\": [\n {\n \"output_type\": \"execute_result\",\n \"data\": {\n \"text/plain\": [\n \" ID MSSubClass LotArea Street HouseStyle ExterQual BldgType \\\\\\n\",\n \"0 1 60 8450 Pave 2Story Gd 1Fam \\n\",\n \"1 2 20 9600 Pave 1Story TA 1Fam \\n\",\n \"2 3 60 11250 Pave 2Story Gd 1Fam \\n\",\n \"3 4 70 9550 Pave 2Story TA 1Fam \\n\",\n \"4 5 60 14260 Pave 2Story Gd 1Fam \\n\",\n \"... ... ... ... ... ... ... ... \\n\",\n \"1163 1164 90 12900 Pave SFoyer TA Duplex \\n\",\n \"1164 1165 80 16157 Pave SLvl TA 1Fam \\n\",\n \"1165 1166 20 9541 Pave 1Story Gd 1Fam \\n\",\n \"1166 1167 20 10475 Pave 1Story Gd 1Fam \\n\",\n \"1167 1168 60 10852 Pave 2Story TA 1Fam \\n\",\n \"\\n\",\n \" LotConfig OverallQual OverallCond ... WoodDeckSF OpenPorchSF \\\\\\n\",\n \"0 Inside 7.0 5.0 ... 0 61 \\n\",\n \"1 FR2 6.0 8.0 ... 298 0 \\n\",\n \"2 Inside 7.0 5.0 ... 0 42 \\n\",\n \"3 Corner 7.0 5.0 ... 0 35 \\n\",\n \"4 FR2 8.0 5.0 ... 192 84 \\n\",\n \"... ... ... ... ... ... ... \\n\",\n \"1163 Inside 4.0 4.0 ... 120 0 \\n\",\n \"1164 FR2 5.0 7.0 ... 168 180 \\n\",\n \"1165 Inside 7.0 5.0 ... 0 114 \\n\",\n \"1166 Corner 8.0 5.0 ... 160 33 \\n\",\n \"1167 Inside 6.0 5.0 ... 0 38 \\n\",\n \"\\n\",\n \" EnclosedPorch 3SsnPorch ScreenPorch PoolArea MiscVal MoSold \\\\\\n\",\n \"0 0 0 0 0 0 2 \\n\",\n \"1 0 0 0 0 0 5 \\n\",\n \"2 0 0 0 0 0 9 \\n\",\n \"3 272 0 0 0 0 2 \\n\",\n \"4 0 0 0 0 0 12 \\n\",\n \"... ... ... ... ... ... ... \\n\",\n \"1163 0 0 0 0 0 1 \\n\",\n \"1164 0 0 0 0 0 6 \\n\",\n \"1165 0 0 0 0 0 9 \\n\",\n \"1166 0 0 0 0 0 2 \\n\",\n \"1167 0 0 0 0 0 2 \\n\",\n \"\\n\",\n \" YrSold SalePrice \\n\",\n \"0 2008 208500 \\n\",\n \"1 2007 181500 \\n\",\n \"2 2008 223500 \\n\",\n \"3 2006 140000 \\n\",\n \"4 2008 250000 \\n\",\n \"... ... ... \\n\",\n \"1163 2008 108959 \\n\",\n \"1164 2007 194000 \\n\",\n \"1165 2009 233170 \\n\",\n \"1166 2010 245350 \\n\",\n \"1167 2006 173000 \\n\",\n \"\\n\",\n \"[1168 rows x 40 columns]\"\n ],\n \"text/html\": [\n \"\\n\",\n \"
\\n\",\n \"
\\n\",\n \"
\\n\",\n \"\\n\",\n \"\\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \"
IDMSSubClassLotAreaStreetHouseStyleExterQualBldgTypeLotConfigOverallQualOverallCond...WoodDeckSFOpenPorchSFEnclosedPorch3SsnPorchScreenPorchPoolAreaMiscValMoSoldYrSoldSalePrice
01608450Pave2StoryGd1FamInside7.05.0...0610000022008208500
12209600Pave1StoryTA1FamFR26.08.0...29800000052007181500
236011250Pave2StoryGd1FamInside7.05.0...0420000092008223500
34709550Pave2StoryTA1FamCorner7.05.0...035272000022006140000
456014260Pave2StoryGd1FamFR28.05.0...1928400000122008250000
..................................................................
116311649012900PaveSFoyerTADuplexInside4.04.0...12000000012008108959
116411658016157PaveSLvlTA1FamFR25.07.0...1681800000062007194000
11651166209541Pave1StoryGd1FamInside7.05.0...01140000092009233170
116611672010475Pave1StoryGd1FamCorner8.05.0...160330000022010245350
116711686010852Pave2StoryTA1FamInside6.05.0...0380000022006173000
\\n\",\n \"

1168 rows × 40 columns

\\n\",\n \"
\\n\",\n \" \\n\",\n \" \\n\",\n \" \\n\",\n \"\\n\",\n \" \\n\",\n \"
\\n\",\n \"
\\n\",\n \" \"\n ]\n },\n \"metadata\": {},\n \"execution_count\": 212\n }\n ]\n },\n {\n \"cell_type\": \"code\",\n \"source\": [\n \"# Mean Squared Error Loss/Cost function\\n\",\n \"def mse_loss(h, y):\\n\",\n \" sq_error = (h - y)**2\\n\",\n \" n = len(y)\\n\",\n \" return 1.0 / (2*n) * sq_error.sum()\\n\",\n \"\\n\",\n \"# Linear Regression class to train our model\\n\",\n \"class Linear_Regression:\\n\",\n \" \\n\",\n \" def predict(self, X): # predict function which models the linear regression\\n\",\n \" return np.dot(X, self.Weight)\\n\",\n \" \\n\",\n \" def gradient_descent(self, X, targets, lr): # gradient descent to update the weights \\n\",\n \"\\n\",\n \" predictions = self.predict(X)\\n\",\n \" \\n\",\n \" error = predictions - targets\\n\",\n \" gradient = np.dot(X.T, error) / len(X)\\n\",\n \"\\n\",\n \" self.Weight -= lr * gradient\\n\",\n \" \\n\",\n \" def fit(self, X, y, n_iter=1000, lr=0.005): # to fit the data as per given max_iterations and learning rate\\n\",\n \"\\n\",\n \" self.Weight = np.zeros(X.shape[1])\\n\",\n \"\\n\",\n \" self.losses = []\\n\",\n \" self.weight_history = [self.Weight]\\n\",\n \" for i in range(n_iter):\\n\",\n \" \\n\",\n \" prediction = self.predict(X)\\n\",\n \" cost = mse_loss(prediction, y)\\n\",\n \" \\n\",\n \" self.losses.append(cost)\\n\",\n \" \\n\",\n \" self.gradient_descent(X_train, y, lr)\\n\",\n \" \\n\",\n \" self.weight_history.append(self.Weight.copy()) # saving the losses at each step for plotting a graph in the end\\n\",\n \" return self\"\n ],\n \"metadata\": {\n \"id\": \"geovFX-hWEWH\"\n },\n \"execution_count\": 213,\n \"outputs\": []\n },\n {\n \"cell_type\": \"code\",\n \"source\": [\n \"# Using Simple Linear Regression with GrLivArea as the independent variable to predict the SalePrice\\n\",\n \"\\n\",\n \"X_train = data_train['GrLivArea']\\n\",\n \"Y_train = data_train['SalePrice']\\n\",\n \"\\n\",\n \"X_test = data_test['GrLivArea']\\n\",\n \"Y_test = data_test['SalePrice']\\n\"\n ],\n \"metadata\": {\n \"id\": \"dDKfrVSzNRtl\"\n },\n \"execution_count\": 224,\n \"outputs\": []\n },\n {\n \"cell_type\": \"code\",\n \"source\": [\n \"# Plotting GrLivArea vs SalePrice to see the relationship between the two indicators\\n\",\n \"df = pd.concat([data_train['SalePrice'], data_train['GrLivArea']], axis=1)\\n\",\n \"df.plot.scatter(x='GrLivArea', y='SalePrice', ylim=(0,800000), s=32);\"\n ],\n \"metadata\": {\n \"id\": \"p59zI5MQOrOL\",\n \"outputId\": \"d1073a13-7152-4f3c-a833-2fc661179f48\",\n \"colab\": {\n \"base_uri\": \"https://localhost:8080/\",\n \"height\": 451\n }\n },\n \"execution_count\": 223,\n \"outputs\": [\n {\n \"output_type\": \"stream\",\n \"name\": \"stderr\",\n \"text\": [\n \"WARNING:matplotlib.axes._axes:*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*. Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\\n\"\n ]\n },\n {\n \"output_type\": \"display_data\",\n \"data\": {\n \"text/plain\": [\n \"
\"\n ],\n \"image/png\": \"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\\n\"\n },\n \"metadata\": {\n \"needs_background\": \"light\"\n }\n }\n ]\n },\n {\n \"cell_type\": \"code\",\n \"source\": [\n \"# standardization helps in convergence of the gradient descent algorithm\\n\",\n \"def standardization (x):\\n\",\n \" x = (x - x.mean()) / x.std()\\n\",\n \" x = np.c_[np.ones(x.shape[0]), x] \\n\",\n \" return x\\n\",\n \"\\n\",\n \"X_train = standardization(X_train)\\n\",\n \"X_test = standardization(X_test)\"\n ],\n \"metadata\": {\n \"id\": \"RoMe71QpOoWf\"\n },\n \"execution_count\": 225,\n \"outputs\": []\n },\n {\n \"cell_type\": \"code\",\n \"source\": [\n \"# fit the training data to the Simple Linear Regression model\\n\",\n \"m1 = Linear_Regression()\\n\",\n \"m1.fit(X_train, Y_train)\\n\",\n \"\\n\",\n \"# Plot the losses calcuated after each iteration\\n\",\n \"plt.title('Cost Function for Simple Linear Regression')\\n\",\n \"plt.xlabel('No. of iterations')\\n\",\n \"plt.ylabel('Cost')\\n\",\n \"plt.plot(m1.losses)\\n\",\n \"plt.show()\"\n ],\n \"metadata\": {\n \"id\": \"Kg4Q4ienR8nn\",\n \"outputId\": \"694a8916-e1c1-45c3-fbd0-7b08fa2074ad\",\n \"colab\": {\n \"base_uri\": \"https://localhost:8080/\",\n \"height\": 427\n }\n },\n \"execution_count\": 226,\n \"outputs\": [\n {\n \"output_type\": \"display_data\",\n \"data\": {\n \"text/plain\": [\n \"
\"\n ],\n \"image/png\": \"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\\n\"\n },\n \"metadata\": {\n \"needs_background\": \"light\"\n }\n }\n ]\n },\n {\n \"cell_type\": \"code\",\n \"source\": [\n \"# get the predictions on the Test data\\n\",\n \"Y_pred = m1.predict(X_test)\\n\",\n \"# find the error\\n\",\n \"SLR_test_error = mse_loss(Y_pred, Y_test)**0.5\\n\",\n \"SLR_test_error\"\n ],\n \"metadata\": {\n \"id\": \"574X51DDSwCV\",\n \"outputId\": \"3a5d55ff-98a2-4b42-b602-900e57cda671\",\n \"colab\": {\n \"base_uri\": \"https://localhost:8080/\"\n }\n },\n \"execution_count\": 218,\n \"outputs\": [\n {\n \"output_type\": \"execute_result\",\n \"data\": {\n \"text/plain\": [\n \"44742.361318569885\"\n ]\n },\n \"metadata\": {},\n \"execution_count\": 218\n }\n ]\n },\n {\n \"cell_type\": \"code\",\n \"source\": [\n \"# Using Mutliple features instead of single feature to model the SalePrice\\n\",\n \"# Multiple Linear Regression\\n\",\n \"X_train = data_train[['LotArea','GrLivArea', 'GarageArea','OverallQual','OverallCond']]\\n\",\n \"X_test = data_test[['LotArea','GrLivArea', 'GarageArea','OverallQual','OverallCond']]\\n\",\n \"\\n\",\n \"# standardize the data\\n\",\n \"X_train = standardization(X_train)\\n\",\n \"X_test = standardization(X_test)\\n\",\n \"\\n\",\n \"# plot the realtion between the price and various factors\\n\",\n \"df = pd.concat([data_train['SalePrice'], data_train['OverallQual']], axis=1)\\n\",\n \"df.plot.scatter(x='OverallQual', y='SalePrice', ylim=(0,800000), s=32);\\n\",\n \"\\n\",\n \"df = pd.concat([data_train['SalePrice'], data_train['OverallCond']], axis=1)\\n\",\n \"df.plot.scatter(x='OverallCond', y='SalePrice', ylim=(0,800000), s=32);\\n\",\n \"\\n\",\n \"df = pd.concat([data_train['SalePrice'], data_train['GarageArea']], axis=1)\\n\",\n \"df.plot.scatter(x='GarageArea', y='SalePrice', ylim=(0,800000), s=32);\"\n ],\n \"metadata\": {\n \"id\": \"3VyIqYV0Tuw2\",\n \"outputId\": \"92af981b-19a1-41cf-d3d3-564b144deb30\",\n \"colab\": {\n \"base_uri\": \"https://localhost:8080/\",\n \"height\": 1000\n }\n },\n \"execution_count\": 227,\n \"outputs\": [\n {\n \"output_type\": \"stream\",\n \"name\": \"stderr\",\n \"text\": [\n \"WARNING:matplotlib.axes._axes:*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*. Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\\n\",\n \"WARNING:matplotlib.axes._axes:*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*. Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\\n\",\n \"WARNING:matplotlib.axes._axes:*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*. Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\\n\"\n ]\n },\n {\n \"output_type\": \"display_data\",\n \"data\": {\n \"text/plain\": [\n \"
\"\n ],\n \"image/png\": \"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\\n\"\n },\n \"metadata\": {\n \"needs_background\": \"light\"\n }\n },\n {\n \"output_type\": \"display_data\",\n \"data\": {\n \"text/plain\": [\n \"
\"\n ],\n \"image/png\": \"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\\n\"\n },\n \"metadata\": {\n \"needs_background\": \"light\"\n }\n },\n {\n \"output_type\": \"display_data\",\n \"data\": {\n \"text/plain\": [\n \"
\"\n ],\n \"image/png\": \"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\\n\"\n },\n \"metadata\": {\n \"needs_background\": \"light\"\n }\n }\n ]\n },\n {\n \"cell_type\": \"code\",\n \"source\": [\n \"# fit the training data to the Multiple Linear Regression Model\\n\",\n \"m2 = Linear_Regression()\\n\",\n \"m2.fit(X_train, Y_train)\\n\",\n \"\\n\",\n \"# Plot the losses calcuated after each iteration\\n\",\n \"plt.title('Cost Function for Multiple Linear Regression')\\n\",\n \"plt.xlabel('No. of iterations')\\n\",\n \"plt.ylabel('Cost')\\n\",\n \"plt.plot(m2.losses)\\n\",\n \"plt.show()\"\n ],\n \"metadata\": {\n \"id\": \"siSWI-SeZSle\",\n \"outputId\": \"3803bbd1-979a-446f-e3e6-c80b4720d182\",\n \"colab\": {\n \"base_uri\": \"https://localhost:8080/\",\n \"height\": 427\n }\n },\n \"execution_count\": 228,\n \"outputs\": [\n {\n \"output_type\": \"display_data\",\n \"data\": {\n \"text/plain\": [\n \"
\"\n ],\n \"image/png\": \"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\\n\"\n },\n \"metadata\": {\n \"needs_background\": \"light\"\n }\n }\n ]\n },\n {\n \"cell_type\": \"code\",\n \"source\": [\n \"# get the predictons on the Test data\\n\",\n \"Y_pred = m2.predict(X_test)\\n\",\n \"# find the error\\n\",\n \"MLR_test_error = mse_loss(Y_pred, Y_test)**0.5\\n\",\n \"MLR_test_error\"\n ],\n \"metadata\": {\n \"id\": \"mLH7GfTCVPBD\",\n \"outputId\": \"fb343129-6aaf-4834-a95a-7a892a9db757\",\n \"colab\": {\n \"base_uri\": \"https://localhost:8080/\"\n }\n },\n \"execution_count\": 221,\n \"outputs\": [\n {\n \"output_type\": \"execute_result\",\n \"data\": {\n \"text/plain\": [\n \"34089.38442211798\"\n ]\n },\n \"metadata\": {},\n \"execution_count\": 221\n }\n ]\n }\n ]\n}","dateCreated":"2022-12-15T00:00:00.000Z","url":"https://qa-cdn.tutorbin.com/file_1670824440507image.png","upvoteCount":205,"author":{"@type":"Person","name":"TutorBin","url":"https://tutorbin.com/tutor"}}}}
Question

(1) Runnable codes in Python. (task: 12 marks, instructions and comments: 5 marks, in total 17 marks)