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Название: Analytic Learning Methods for Pattern RecognitionАвтор: Kar-Ann Toh, Huiping Zhuang, Simon Liu, Zhiping Lin
Издательство: Springer
Год: 2025
Страниц: 400
Язык: английский
Формат: pdf (true), epub
Размер: 57.9 MB
This textbook is a consolidation of learning methods which comes in an analytic form. The covered learning methods include classical and advanced solutions to problems of regression, minimum classification error, maximum receiver operating characteristics, bridge regression, ensemble learning and network learning. Both the primal and dual solution forms are discussed for over-and under-determined systems. Such coverage provides an important perspective for handling systems with overwhelming samples or systems with overwhelming parameters. For goal driven classification, the solutions to minimum classification-error, maximum receiver operating characteristics, bridge regression, and ensemble learning represent recent advancements in the literature. Presently, courses in the field of Machine Learning and Artificial Intelligence (AI) place significant emphasis on Deep Learning. Such emphasis assumes that students already possess a solid foundation in the classical aspects of Machine Learning. Includes examples coded in Python and Matlab which provide students and instructors with mathematical insights.
