In [ ]: %matplotlib inline Load the dataset In [ ]: flight_df = pd.read_excel('Airfares.xlsx', sheet_name='data') Prepro

[answerhappygod]

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%matplotlib inline
Load the dataset
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flight_df = pd.read_excel('Airfares.xlsx',sheet_name='data')
Preprocessing¶
1.Conduct preprocessing below using FARE as dependent variableand the following variables as independent variables: COUPON, NEW,VACATION, SW, HI, S_INCOME, E_INCOME, S_POP, E_POP, SLOT, GATE,DISTANCE, PAX. At the end of preprocessing, all independentvariables should be in a dataframe named X and the dependentvariable should be in a Series object(i.e., single-dimensiondataframe) named y.
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2. Check the missing values. Drop them if needed.
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Partition data
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train_X, valid_X, train_y, valid_y = train_test_split(X, y,test_size=0.4, random_state=1)
Train the model
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car_lm = LinearRegression()
Print coefficients
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print('intercept ', car_lm.intercept_)
Test the model using the training set
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Test the model using validation set
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Print performance measures
Compute common accuracy measures
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Determine the residuals and create a histogram
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Exhaustive search
Run an exhaustive search.
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Backward elimination
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Forward selection
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