Unsupervised Learning Approaches for Dimensionality Reduction and - Data Visualizatio

Summary

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.

Product details

• Authors: Shrusti Ghela, Anveshrithaa Sundareswaran, B.K. Tripathy, B.k. (Vellore Institute of Technology Tripathy
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Hardback
• Released: 02.09.2021
• EAN: 9781032041018
• ISBN: 978-1-0-3204101-8
• No. of pages: 160
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; MATHEMATICS / Probability & Statistics / General, TECHNOLOGY & ENGINEERING / Automation, Probability & statistics, Automatic control engineering, Databases, Probability and statistics, COMPUTERS / Database Administration & Management