Unsupervised Learning Approaches for Dimensionality Reduction and Data

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Description & Details

Unsupervised Learning Approaches for Dimensionality Reduction and Data Description

This book describes algorithms like Locally Linear Embedding, Laplacian eigenmaps, Semidefinite Embedding, t-SNE to resolve the problem of dimensionality reduction in case of non-linear relationships within the data. Underlying mathematical concepts, derivations, proofs, strengths and limitations of these algorithms are discussed as well.

Details

OPC PX7SX82
Brand
riachristiecollections
Codes 103204103X (ISBN-10)
9781032041032 (ISBN)
MPN 9781032041032

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