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Hands-On Unsupervised Learning with Python

You're reading from  Hands-On Unsupervised Learning with Python

Product type Book
Published in Feb 2019
Publisher Packt
ISBN-13 9781789348279
Pages 386 pages
Edition 1st Edition
Languages
Author (1):
Giuseppe Bonaccorso Giuseppe Bonaccorso
Profile icon Giuseppe Bonaccorso
Toc

Table of Contents (12) Chapters close

Preface 1. Getting Started with Unsupervised Learning 2. Clustering Fundamentals 3. Advanced Clustering 4. Hierarchical Clustering in Action 5. Soft Clustering and Gaussian Mixture Models 6. Anomaly Detection 7. Dimensionality Reduction and Component Analysis 8. Unsupervised Neural Network Models 9. Generative Adversarial Networks and SOMs 10. Assessments 11. Other Books You May Enjoy

Fuzzy c-means

The first algorithm that we will propose is a variation of k-means that's based on soft assignments. The name Fuzzy c-means derives from the concept of a fuzzy set, which is an extension of classical binary sets (that is, in this case, a sample can belong to a single cluster) to sets based on the superimposition of different subsets representing different regions of the whole set. For example, a set based on the age of some users can have the degrees young, adult, and senior, associated with three different (and partially overlapping) age ranges: 18-35, 28-60, and >50. So, for example, a 30-year-old user is both young and adult, to different degrees (and, indeed, is a borderline user, considering the boundaries). For further details about these kinds of sets and all of the related operations, I suggest the book Concepts and Fuzzy Logic, Belohlavek R., Klir...

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