Clustering: A Data Recovery Approach, Second Edition

✍ Scribed by Boris Mirkin (Author)

Publisher: Chapman and Hall/CRC
Year: 2013
Leaves: 366
Edition: 2
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Often considered more of an art than a science, books on clustering have been dominated by learning through example with techniques chosen almost through trial and error. Even the two most popular, and most related, clustering methods-K-Means for partitioning and Ward`s method for hierarchical clustering-have lacked the theoretical underpinning req

✦ Table of Contents

What Is Clustering. What Is Data. K-Means Clustering and Related Approaches. Least-Squares Hierarchical Clustering. Similarity Clustering: Uniform, Modularity, Additive, Spectral, Consensus and Single Linkage. Validation and Interpretation. Least-Squares Data Recovery Clustering Models.

✦ Subjects

Mathematics & Statistics;Statistics & Probability;Statistics;Statistical Computing;Statistics & Computing

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