Step 2: Data minimization techniques for Supervised Learning
If we want to diminish the amount of data employed by the algorithm, we can think of two possible ways of preprocessing the data:
Reducing the number of features, or
Reducing the number of data points.
In the following pages we will cover a number of techniques for each option:
pageOption 1: Reducing featurespageOption 2: Reducing data pointsLast updated