…aps are much like the United States’ Senate, where every region gets equal (visual) representation. Rhode Island is now the same size as Alaska, but the positioning still allows the audience to understand they are looking at a map visualization of the US.
… than training all of the models in isolation of one another, boosting trains models in succession, with each new model being trained to correct the errors made by the previous ones. Models are added sequentially until no further improvements can be made.
.cut() function from Pandas takes as input a set of
bins which define each range of our If-Else and a set of
labels which define which value to return for each range. It then performs the exact same operation we wrote manually with the
SMOTE’s main advantage compared to traditional random naive over-sampling is that by creating synthetic observations instead of reusing existing observations, your classifier is less likely to overfit. At the same time, you should always make sure that the observations created by SMOTE are realistic.…