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08-DimensionalityReduction

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Dimensionality Reduction

There are two ways to reduce the dimensions of any data set. Either you select some features and discard the others or you create some new features that allow you concisely represent the same amount of information as your existing features.

Feature Selection Feature Extraction
Backward Elimination PCA
Forward Selection LDA
Bidirectional Elimination Kernel PCA
Score Comparison

The things that we will cover in this section are as follows:

  1. Principal Component Analysis
  2. LDA