Linear Discriminant Analysis in Artificial intelligence | (LDA)

The objective of Linear Discriminant Analysis (LDA) is to perform dimensionality reduction while preserving as much of the class discriminatory information as possible

  • Assume we have a set of D-dimensional samples {x(1, x(2, …, x(N}, N1 of which belong to class ω1, and N2 to class ω2. We seek to obtain a scalar y by projecting the samples x onto a line


  • Of all the possible lines we would like to select the one that maximizes the separability of the scalars
Linear Discriminant Analysis | (LDA)
This is illustrated for the two-dimensional case

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