Chapter 3
Predictive Analytics with Ensemble Learning
Section 4
Dealing with Class Imbalance
One of the most common problems we face in the real world is the quality of data. For a classifier to perform well, it needs to see equal number of points for each class. Hence we need to make sure that we account for this imbalance algorithmically. - Define parameters for Extremely Random Forest classifier - Build, train and visualize data - Predict output and compute performance