Narsky I., Porter F.C. Statistical Analysis Techniques in Particle Physics: Fits, Density Estimation and Supervised Learning

Wiley, Weinheim, 2013, 459 pages, ISBN: 3527410864Modern analysis of HEP data needs advanced statistical tools to separate signal from background. This is the first book which focuses on machine learning techniques. It will be of interest to almost every high energy physicist, and, due to its coverage, suitable for students.Why We Wrote This Book and How You Should Read It
Parametric Likelihood Fits
Goodness of Fit
Resampling Techniques
Density Estimation
Basic Concepts and Definitions of Machine Learning
Data Preprocessing
Linear Transformations and Dimensionality Reduction
Introduction to Classification
Assessing Classifier Performance
Linear and Quadratic Discriminant Analysis, Logistic Regression, and Partial Least Squares Regression
Neural Networks
Local Learning and Kernel Expansion
Decision Trees
Ensemble Learning
Reducing Multiclass to Binary
How to Choose the Right Classifier for Your Analysis and Apply It Correctly
Methods for Variable Ranking and Selection
Bump Hunting in Multivariate Data
Software Packages for Machine Learning