multiple_linear_regression.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Multiple Linear Regression","provenance":[],"toc_visible":true,"authorship_tag":"ABX9TyPhYhte6t7H4wEK4xPpDWT7"},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"markdown","metadata":{"id":"CazISR8X_HUG","colab_type":"text"},"source":["# Multiple Linear Regression"]},{"cell_type":"markdown","metadata":{"id":"pOyqYHTk_Q57","colab_type":"text"},"source":["## Importing the libraries"]},{"cell_type":"code","metadata":{"id":"T_YHJjnD_Tja","colab_type":"code","colab":{}},"source":["import numpy as np\n","import matplotlib.pyplot as plt\n","import pandas as pd"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"vgC61-ah_WIz","colab_type":"text"},"source":["## Importing the dataset"]},{"cell_type":"code","metadata":{"id":"UrxyEKGn_ez7","colab_type":"code","colab":{}},"source":["dataset = pd.read_csv('50_Startups.csv')\n","X = dataset.iloc[:, :-1].values\n","y = dataset.iloc[:, -1].values"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"GOB3QhV9B5kD","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":857},"outputId":"4a05377a-2db2-43fc-b824-a0710448baee","executionInfo":{"status":"ok","timestamp":1586353652778,"user_tz":-240,"elapsed":552,"user":{"displayName":"Hadelin de Ponteves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhEuXdT7eQweUmRPW8_laJuPggSK6hfvpl5a6WBaA=s64","userId":"15047218817161520419"}}},"source":["print(X)"],"execution_count":3,"outputs":[{"output_type":"stream","text":["[[165349.2 136897.8 471784.1 'New York']\n"," [162597.7 151377.59 443898.53 'California']\n"," [153441.51 101145.55 407934.54 'Florida']\n"," [144372.41 118671.85 383199.62 'New York']\n"," [142107.34 91391.77 366168.42 'Florida']\n"," [131876.9 99814.71 362861.36 'New York']\n"," [134615.46 147198.87 127716.82 'California']\n"," [130298.13 145530.06 323876.68 'Florida']\n"," [120542.52 148718.95 311613.29 'New York']\n"," [123334.88 108679.17 304981.62 'California']\n"," [101913.08 110594.11 229160.95 'Florida']\n"," [100671.96 91790.61 249744.55 'California']\n"," [93863.75 127320.38 249839.44 'Florida']\n"," [91992.39 135495.07 252664.93 'California']\n"," [119943.24 156547.42 256512.92 'Florida']\n"," [114523.61 122616.84 261776.23 'New York']\n"," [78013.11 121597.55 264346.06 'California']\n"," [94657.16 145077.58 282574.31 'New York']\n"," [91749.16 114175.79 294919.57 'Florida']\n"," [86419.7 153514.11 0.0 'New York']\n"," [76253.86 113867.3 298664.47 'California']\n"," [78389.47 153773.43 299737.29 'New York']\n"," [73994.56 122782.75 303319.26 'Florida']\n"," [67532.53 105751.03 304768.73 'Florida']\n"," [77044.01 99281.34 140574.81 'New York']\n"," [64664.71 139553.16 137962.62 'California']\n"," [75328.87 144135.98 134050.07 'Florida']\n"," [72107.6 127864.55 353183.81 'New York']\n"," [66051.52 182645.56 118148.2 'Florida']\n"," [65605.48 153032.06 107138.38 'New York']\n"," [61994.48 115641.28 91131.24 'Florida']\n"," [61136.38 152701.92 88218.23 'New York']\n"," [63408.86 129219.61 46085.25 'California']\n"," [55493.95 103057.49 214634.81 'Florida']\n"," [46426.07 157693.92 210797.67 'California']\n"," [46014.02 85047.44 205517.64 'New York']\n"," [28663.76 127056.21 201126.82 'Florida']\n"," [44069.95 51283.14 197029.42 'California']\n"," [20229.59 65947.93 185265.1 'New York']\n"," [38558.51 82982.09 174999.3 'California']\n"," [28754.33 118546.05 172795.67 'California']\n"," [27892.92 84710.77 164470.71 'Florida']\n"," [23640.93 96189.63 148001.11 'California']\n"," [15505.73 127382.3 35534.17 'New York']\n"," [22177.74 154806.14 28334.72 'California']\n"," [1000.23 124153.04 1903.93 'New York']\n"," [1315.46 115816.21 297114.46 'Florida']\n"," [0.0 135426.92 0.0 'California']\n"," [542.05 51743.15 0.0 'New York']\n"," [0.0 116983.8 45173.06 'California']]\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"VadrvE7s_lS9","colab_type":"text"},"source":["## Encoding categorical data"]},{"cell_type":"code","metadata":{"id":"wV3fD1mbAvsh","colab_type":"code","colab":{}},"source":["from sklearn.compose import ColumnTransformer\n","from sklearn.preprocessing import OneHotEncoder\n","ct = ColumnTransformer(transformers=[('encoder', OneHotEncoder(), [3])], remainder='passthrough')\n","X = np.array(ct.fit_transform(X))"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"4ym3HdYeCGYG","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":857},"outputId":"ce09e670-cf06-4a1c-f5b0-89422aae0496","executionInfo":{"status":"ok","timestamp":1586353657759,"user_tz":-240,"elapsed":616,"user":{"displayName":"Hadelin de Ponteves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhEuXdT7eQweUmRPW8_laJuPggSK6hfvpl5a6WBaA=s64","userId":"15047218817161520419"}}},"source":["print(X)"],"execution_count":5,"outputs":[{"output_type":"stream","text":["[[0.0 0.0 1.0 165349.2 136897.8 471784.1]\n"," [1.0 0.0 0.0 162597.7 151377.59 443898.53]\n"," [0.0 1.0 0.0 153441.51 101145.55 407934.54]\n"," [0.0 0.0 1.0 144372.41 118671.85 383199.62]\n"," [0.0 1.0 0.0 142107.34 91391.77 366168.42]\n"," [0.0 0.0 1.0 131876.9 99814.71 362861.36]\n"," [1.0 0.0 0.0 134615.46 147198.87 127716.82]\n"," [0.0 1.0 0.0 130298.13 145530.06 323876.68]\n"," [0.0 0.0 1.0 120542.52 148718.95 311613.29]\n"," [1.0 0.0 0.0 123334.88 108679.17 304981.62]\n"," [0.0 1.0 0.0 101913.08 110594.11 229160.95]\n"," [1.0 0.0 0.0 100671.96 91790.61 249744.55]\n"," [0.0 1.0 0.0 93863.75 127320.38 249839.44]\n"," [1.0 0.0 0.0 91992.39 135495.07 252664.93]\n"," [0.0 1.0 0.0 119943.24 156547.42 256512.92]\n"," [0.0 0.0 1.0 114523.61 122616.84 261776.23]\n"," [1.0 0.0 0.0 78013.11 121597.55 264346.06]\n"," [0.0 0.0 1.0 94657.16 145077.58 282574.31]\n"," [0.0 1.0 0.0 91749.16 114175.79 294919.57]\n"," [0.0 0.0 1.0 86419.7 153514.11 0.0]\n"," [1.0 0.0 0.0 76253.86 113867.3 298664.47]\n"," [0.0 0.0 1.0 78389.47 153773.43 299737.29]\n"," [0.0 1.0 0.0 73994.56 122782.75 303319.26]\n"," [0.0 1.0 0.0 67532.53 105751.03 304768.73]\n"," [0.0 0.0 1.0 77044.01 99281.34 140574.81]\n"," [1.0 0.0 0.0 64664.71 139553.16 137962.62]\n"," [0.0 1.0 0.0 75328.87 144135.98 134050.07]\n"," [0.0 0.0 1.0 72107.6 127864.55 353183.81]\n"," [0.0 1.0 0.0 66051.52 182645.56 118148.2]\n"," [0.0 0.0 1.0 65605.48 153032.06 107138.38]\n"," [0.0 1.0 0.0 61994.48 115641.28 91131.24]\n"," [0.0 0.0 1.0 61136.38 152701.92 88218.23]\n"," [1.0 0.0 0.0 63408.86 129219.61 46085.25]\n"," [0.0 1.0 0.0 55493.95 103057.49 214634.81]\n"," [1.0 0.0 0.0 46426.07 157693.92 210797.67]\n"," [0.0 0.0 1.0 46014.02 85047.44 205517.64]\n"," [0.0 1.0 0.0 28663.76 127056.21 201126.82]\n"," [1.0 0.0 0.0 44069.95 51283.14 197029.42]\n"," [0.0 0.0 1.0 20229.59 65947.93 185265.1]\n"," [1.0 0.0 0.0 38558.51 82982.09 174999.3]\n"," [1.0 0.0 0.0 28754.33 118546.05 172795.67]\n"," [0.0 1.0 0.0 27892.92 84710.77 164470.71]\n"," [1.0 0.0 0.0 23640.93 96189.63 148001.11]\n"," [0.0 0.0 1.0 15505.73 127382.3 35534.17]\n"," [1.0 0.0 0.0 22177.74 154806.14 28334.72]\n"," [0.0 0.0 1.0 1000.23 124153.04 1903.93]\n"," [0.0 1.0 0.0 1315.46 115816.21 297114.46]\n"," [1.0 0.0 0.0 0.0 135426.92 0.0]\n"," [0.0 0.0 1.0 542.05 51743.15 0.0]\n"," [1.0 0.0 0.0 0.0 116983.8 45173.06]]\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"WemVnqgeA70k","colab_type":"text"},"source":["## Splitting the dataset into the Training set and Test set"]},{"cell_type":"code","metadata":{"id":"Kb_v_ae-A-20","colab_type":"code","colab":{}},"source":["from sklearn.model_selection import train_test_split\n","X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 0)"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"k-McZVsQBINc","colab_type":"text"},"source":["## Training the Multiple Linear Regression model on the Training set"]},{"cell_type":"code","metadata":{"id":"ywPjx0L1BMiD","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":34},"outputId":"099836bc-4d85-4b4f-a488-093faf02e8cb","executionInfo":{"status":"ok","timestamp":1586353664008,"user_tz":-240,"elapsed":757,"user":{"displayName":"Hadelin de Ponteves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhEuXdT7eQweUmRPW8_laJuPggSK6hfvpl5a6WBaA=s64","userId":"15047218817161520419"}}},"source":["from sklearn.linear_model import LinearRegression\n","regressor = LinearRegression()\n","regressor.fit(X_train, y_train)"],"execution_count":7,"outputs":[{"output_type":"execute_result","data":{"text/plain":["LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)"]},"metadata":{"tags":[]},"execution_count":7}]},{"cell_type":"markdown","metadata":{"id":"xNkXL1YQBiBT","colab_type":"text"},"source":["## Predicting the Test set results"]},{"cell_type":"code","metadata":{"id":"TQKmwvtdBkyb","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":185},"outputId":"493436bf-a4ae-4374-ca16-0b0c25d19457","executionInfo":{"status":"ok","timestamp":1586353666678,"user_tz":-240,"elapsed":951,"user":{"displayName":"Hadelin de Ponteves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhEuXdT7eQweUmRPW8_laJuPggSK6hfvpl5a6WBaA=s64","userId":"15047218817161520419"}}},"source":["y_pred = regressor.predict(X_test)\n","np.set_printoptions(precision=2)\n","print(np.concatenate((y_pred.reshape(len(y_pred),1), y_test.reshape(len(y_test),1)),1))"],"execution_count":8,"outputs":[{"output_type":"stream","text":["[[103015.2  103282.38]\n"," [132582.28 144259.4 ]\n"," [132447.74 146121.95]\n"," [ 71976.1   77798.83]\n"," [178537.48 191050.39]\n"," [116161.24 105008.31]\n"," [ 67851.69  81229.06]\n"," [ 98791.73  97483.56]\n"," [113969.44 110352.25]\n"," [167921.07 166187.94]]\n"],"name":"stdout"}]}]}