Error estimation for pattern recognition

This book is the first of its kind to discuss error estimation with a model-based approach. From the basics of classifiers and error estimators to more specialized classifiers, it covers important topics and essential issues pertaining to the scientific validity of pattern classification. Additional features of the book include: * The latest results on the accuracy of error estimation * Performance analysis of resubstitution, cross-validation, and bootstrap error estimators using analytical and simulation approaches * Highly interactive computer-based exercises and end-of-chapter problems