This book is a thorough introduction to the most important topics in data mining and machine learning. It begins with a detailed review of classical function estimation and proceeds with chapters on nonlinear regression, classification, and ensemble methods. The final chapters focus on clustering, dimension reduction, variable selection, and...

Assuming minimal background on the part of students, this text gradually develops the principles of basic real analysis and presents the background necessary to understand applications used in such disciplines as statistics, operations research, and engineering. The text presents the first elementary exposition of the gauge integral and...

• Write customizable scripts that are easy to adjust to suit the needs of different projects
• Combine your knowledge of modular scripting elements to build a complete...

Based on the author's lecture notes and research, this well-illustrated and comprehensive text is one of the first to provide an introduction to image registration with particular emphasis on numerical methods in medical imaging. Ideal for researchers in industry and academia, it is also a suitable study guide for graduate mathematicians,...

This text demonstrates how to extract knowledge by finding meaningful connections among data spread throughout the Web. Readers learn methods and algorithms from the fields of information retrieval, machine learning, and data mining which, when combined, provide a solid...

This book has a long history. It began over two decades ago as the first half of a book on information and ergodic theory. The intent was and remains to provide a reasonably self-contained advanced (at least for engineers) treatment of measure theory, probability theory, and random processes, with an emphasis on general alphabets and on ergodic...

This book is primarily designed for a senior undergraduate class in Categorical Data Analysis and for majors in biomedical, biostatistics and statistics programs, but can also be used as reference text for researchers working in the area, and /or for an introductory text in a graduate course on the subject. A prerequisite of a one year...

Jitter, noise, and bit error (JNB) and signal integrity (SI) have become today‘s greatest challenges in high-speed digital design. Now, there’s a...

Five years ago, we authored “Text Mining: Predictive Methods for Analyzing Unstructured Information.” That book was geared mostly to professional practitioners, but was adaptable to course work with some effort by the instructor. Many topics were evolving, and this was one of the earliest efforts to collect material for predictive...

Principles of Data Mining explains and explores the principal techniques of Data Mining: for classification, association rule mining and clustering. Each...