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Book synopsis

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.

Book details

• Full title: Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization
• Subtitle: Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization
• Author: Tripathy, B.K. (Vellore Institute of Technology, Vellore, India.), Sundareswaran, Anveshrithaa (Vellore Institute of Technology, India.), Ghela, Shrusti (Vellore Institute of Technology, India.)
• Language: English
• Binding: Paperback
• Number of pages: 160
• EAN: 9781032041032
• ID: 43908044
• Publisher: Taylor & Francis Ltd
• Weight: 453 g
• Dimensions: 234 × 156 mm
• Date of publishing: 25. September 2023

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