Robustness in Statistical Pattern Recognition
By: by Yurij Kharin
Series: Mathematics and Its Applications -- 380; Mathematics and Its Applications -- 380
Publisher: Springer Netherlands
Published: 1996
Place of publication: Dordrecht
Language: eng
Format: [electronic resource] /
Number of pages: 302
ISBN-13: 9789048147601; 9789401586306
Subjects: Mathematics; Statistics; Artificial intelligence
Description: This monograph is devoted to problems of robust (stable) statistical pattern recognition. Experimental data to be classified usually deviate from assumed hypothetical probability models of the data. In such cases traditional decision rules constructed by means of the classical pattern recognition theory based on a fixed hypothetical model of the data often become non-stable, and the classification risk increases non-controllably. The book concentrates on three main problems: robustness evaluation for classical decision rules in the presence of distortion; estimation of critical levels of distortions for given values of the robustness factor; and the construction of robust decision rules with stable classification risk regarding certain types of distortions. Theoretical results are illustrated by computer modelling and by application to medical diagnostics. Audience: This volume is primarily intended for mathematicians, statisticians, and engineers in applied mathematics, computer science and cybernetics. It is also recommended as a textbook for a one-semester course for advanced undergraduate and graduate students training in the indicated fields.
Notes: Online full text is restricted to subscribers.

Also available in print.

Mode of access: World Wide Web.