Designed for social and behavioral scientists, this book introduces R through the Tidyverse, catering to those with no prior experience in programming or the software. It targets advanced undergraduates, graduate students, and seasoned practitioners, providing a comprehensive foundation for utilizing R in research. The authors focus on practical applications, ensuring readers can effectively apply their skills in real-world scenarios.
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.
Dimension reduction offers researchers and scholars the ability to make complex, high dimensional data spaces simpler and more manageable. This Element offers readers a suite of modern unsupervised dimension reduction techniques to efficiently represent the original high dimensional data space in a simplified, lower dimensional subspace.