关于统计学习入门书籍，很经典！ T. Hastie, R. Tibshirani, J. Friedman, “The Elements of statistical Learning: Data Mining, Inference, and Prediction”, 2001, Springer-Verlag
This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readers Models for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamenta
Signal processing and neural computation have separately and significantly influenced many disciplines, but the cross-fertilization of the two fields has begun only recently. Research now shows that each has much to teach the other, as we see highly
This volume describes the essential tools and techniques of statistical signal processing. At every stage, theoretical ideas are linked to specific applications in communications and signal processing. The book begins with an overview of basic proba
Most statistical work is concerned directly with the provision and implementation of methods for study design and for the analysis and interpretation of data. The theory of statistics deals in principle with the general concepts underlying all aspec
Preface . 1 Introduction 2 Overview of Supervised Learning 2.1 Introduction 2.2 Variable Types and Terminology 2.3 Two Simple Approaches to Prediction: Least Squares and Nearest Neighbors 2.4 Statistical Decision Theory 2.5 Lo.cal Methods in High Di
There are two approaches to undergraduate and graduate courses in linear statistical models and experimental design in applied statistics. One is a two-term sequence focusing on regression followed by ANOVA/Experimental design. Applied Linear Statis
