Tree Features

The idea of Tree Features is to train a relatively simple tree on the data and add prediction timestamp as one of the features. As a tree model can be used also for feature importance, we can know how the time affects the data and at which point. Moreover, we can look at the split created by the timestamp and we can see the difference between the concepts before and after the split.

Concept drift detection method

In the image above we can see that the date feature is at the root and that means that this feature has the highest information gain, so that means that on the July 22nd their may have occurred a drift in the data.

Start Monitoring Your Models in Minutes