Sebastian Raschka • 8/3/2014

Linear Discriminant Analysis

This article provides a detailed, step-by-step explanation of Linear Discriminant Analysis (LDA), a supervised dimensionality reduction technique used in machine learning and pattern classification. It contrasts LDA with Principal Component Analysis (PCA), outlines the mathematical steps involved (including scatter matrices and eigenvalue problems), and demonstrates its application using the Iris dataset for improved class separability and reduced overfitting.

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#Machine Learning #dimensionality reduction #classification