<p>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<br>pertaining to the scientific validity of pattern classification.<br><br><b>Additional features of the book include:</b></p><ul><li>The latest results on the accuracy of error estimation </li><li>Performance analysis of resubstitution, cross-validation, and bootstrap error estimators using analytical and simulation approaches</li><li>Highly interactive computer-based exercises and end-of-chapter problems </li></ul>