Hands-On Data Science for Marketing

Linear regression

Similar to the previous chapter, we are going to split the sample set into train and test sets, using the following code:

from sklearn.model_selection import train_test_splittarget_var = 'CLV_'+clv_freqall_features = [x for x in sample_set_df.columns if x not in ['CustomerID', target_var]]x_train, x_test, y_train, y_test = train_test_split(    sample_set_df[all_features],     sample_set_df[target_var],     test_size=0.3)

As you can see from this code, we are taking 70% of the sample set for training the model and the remaining 30% for testing and evaluating the model performance. In this section, we will be using a linear regression model. However, we recommend experimenting with other machine learning algorithms, such as random ...