Term tag: feature selection

Feature Scaling

Feature scaling puts numeric features on comparable ranges so no variable dominates by its units alone — why distance- and gradient-based models need it.

Feature Selection (FS)

Which columns to keep and how to decide: filter vs wrapper vs embedded, why 2^n subsets rules out brute force, and the CV mistake that fakes accuracy.

Information Gain

Entropy worked from scratch, one split computed by hand in bits, and why a unique ID column scores the maximum possible information gain.