Error Estimation for Pattern Recognition (Hardcover)

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

這本書是第一本以模型為基礎的方法來討論誤差估計的書籍。從分類器和誤差估計器的基礎知識到更專門的分類器，它涵蓋了與模式分類的科學有效性相關的重要主題和基本問題。

本書的其他特點包括：
- 關於誤差估計準確性的最新研究結果
- 使用分析和模擬方法對重新歸入、交叉驗證和自助法誤差估計器的性能分析
- 高度互動的基於電腦的練習和章節結束問題