Unsupervised Machine Learning for Clustering in Political and Social Research

Offers researchers and teachers an introduction to clustering, which is a prominent class of unsupervised machine learning for exploring and understanding latent, non-random structure in data. A suite of widely used clustering techniques is covered, in addition to R code and real data to facilitate interaction with the concepts.

• | : Philip D. Waggoner (University of Chicago)
• | Publisher: Cambridge University Press
• | Publication Date: Jan 28, 2021
• | Country of Publication: United Kingdom
• | Number of Pages: 75 pages
• | Language: Unknown
• | Binding: Paperback / softback
• | ISBN-10: 110879338X
• | ISBN-13: 9781108793384