Apache Spark Deep Learning Cookbook

How to do it...

1. Drop the Price column from the x_df dataframe and save it into a new dataframe named x_df2 using the following script:

 x_df2 = x_df.drop(['price'], axis = 1)

2. Declare a variable named reg and equate it to the LinearRegression() function from the Scikit Learn library using the following script:

 reg=linear_model.LinearRegression()

3. Split the dataset into test and train using the following script:

 x_train,x_test,y_train,y_test = train_test_split(x_df2,y_df,test_size=0.4,random_state=4)

4. Fit the model over the training set using the following script:

 reg.fit(x_train,y_train)

5. Print the coefficients generated from applying linear regression to the training and test sets by using the reg.coef_ command.
6. Take a look at the ...