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Название: Assessing and Improving Prediction and Classification: Theory and Algorithms in C++
Автор: Timothy Masters
Издательство: Apress
Год: 2018
Страниц: 517
Формат: True PDF
Размер: 10 Mb
Язык: English
Assess the quality of your prediction and classification models in ways that accurately reflect their real-world performance, and then improve this performance using state-of-the-art algorithms such as committee-based decision making, resampling the dataset, and boosting. This book presents many important techniques for building powerful, robust models and quantifying their expected behavior when put to work in your application.