29 lines
905 B
Python
29 lines
905 B
Python
# Data Preprocessing
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import pandas as pd
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import numpy as np
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import matplotlib.pyplot as plt
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dataset = pd.read_csv('../datasets/studentscores.csv')
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X = dataset.iloc[ : , : 1 ].values
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Y = dataset.iloc[ : , 1 ].values
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from sklearn.model_selection import train_test_split
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X_train, X_test, Y_train, Y_test = train_test_split( X, Y, test_size = 1/4, random_state = 0)
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# Fitting Simple Linear Regression Model to the training set
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from sklearn.linear_model import LinearRegression
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regressor = LinearRegression()
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regressor = regressor.fit(X_train, Y_train)
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# Predecting the Result
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Y_pred = regressor.predict(X_test)
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# Visualising the Training results
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plt.scatter(X_train , Y_train, color = 'red')
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plt.plot(X_train , regressor.predict(X_train), color ='blue')
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# Visualizing the test results
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plt.scatter(X_test , Y_test, color = 'red')
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plt.plot(X_test , regressor.predict(X_test), color ='blue')
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plt.show()
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