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Linear Discriminant Analysis

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May 1, 2024 3 minute read

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Linear Discriminant Analysis (LDA) is a statistical technique used for dimensionality reduction and classification. It is often used in machine learning and pattern recognition, as it can improve the performance of predictive models by reducing the number of input features and increasing the separability between different classes.

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We've selected four books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Linear Discriminant Analysis.

Deep Learning for Vision Systems

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An up-to-date guide to LDA for machine learning practitioners. It covers advanced topics such as kernel LDA and sparse LDA.

Deep Learning for Vision Systems

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Deep Learning for Vision Systems

Kindle Edition

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