3 docs tagged with "Feature Engineering"

Let's divide the train data into x and y now that it has been cleaned and preprocessed.

Three features are engineered: Impression Rate (number of impressions / total cost), Click-Through Rate (CTR) (number of clicks / total impressions), and Conversion Rate (number of conversions / total clicks). There are some NaN and Inf values due to division by 0 in some cases – these are filled with 0.

After cleaning and preprocessing the data, we created the relevant and important features for forecasting.