Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer perceptrons -- Local models -- Kernel machine…
"This book focuses on a few of the most important clustering algorithms, providing a detailed account of these major models in an information retrieval context. The beginning chapters introduce the classic algorithms in detail, while the later chapters describe clustering throug…
"This edition provides a thorough revision of the fourth edition which focuses on the practical aspects of cluster analysis and covers new methodology in terms of longitudinal data and provides examples from bioinformatics. Real life examples are used throughout to demonstrate t…
"This edition provides a thorough revision of the fourth edition which focuses on the practical aspects of cluster analysis and covers new methodology in terms of longitudinal data and provides examples from bioinformatics. Real life examples are used throughout to demonstrate t…
"This edition provides a thorough revision of the fourth edition which focuses on the practical aspects of cluster analysis and covers new methodology in terms of longitudinal data and provides examples from bioinformatics. Real life examples are used throughout to demonstrate t…
"This edition provides a thorough revision of the fourth edition which focuses on the practical aspects of cluster analysis and covers new methodology in terms of longitudinal data and provides examples from bioinformatics. Real life examples are used throughout to demonstrate t…
How do we group different subjects on a variety of variables? Kenneth Bailey addresses such questions and shows how classification methods can be used to improve research.
How do we group different subjects on a variety of variables? Kenneth Bailey addresses such questions and shows how classification methods can be used to improve research.
