Examining the Relationships Between Features and the Response Variable
In order to make accurate predictions of the response variable, good features are necessary. We need features that are clearly linked to the response variable in some way. Thus far, we've examined the relationship between a couple of features and the response variable, either by calculating the groupby
/mean
of a feature and the response variable, or using individual features in a model and examining performance. However, we have not yet done a systematic exploration of how all the features relate to the response variable. We will do that now and begin to capitalize on all the hard work we put in when we were exploring the features and making sure the data quality was good.
A popular way of getting a quick look at how all the features relate to the response variable, as well as how the features are related to each other, is by using a correlation plot. We will first create a correlation plot for the case...