{"product_id":"jin-yaochu-multi-objective-machine-learning-9783540306764","title":"Multi-Objective Machine Learning","description":"Recently, increasing interest has been shown in applying the concept of Pareto-optimality to machine learning, particularly inspired by the successful developments in evolutionary multi-objective optimization. It has been shown that the multi-objective approach to machine learning is particularly successful to improve the performance of the traditional single objective machine learning methods, to generate highly diverse multiple Pareto-optimal models for constructing ensembles models and, and to achieve a desired trade-off between accuracy and interpretability of neural networks or fuzzy systems. This monograph presents a selected collection of research work on multi-objective approach to machine learning, including multi-objective feature selection, multi-objective model selection in training multi-layer perceptrons, radial-basis-function networks, support vector machines, decision trees, and intelligent systems.","brand":"Springer Berlin","offers":[{"title":"Default Title","offer_id":53694763958614,"sku":null,"price":0.0,"currency_code":"EUR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0925\/5829\/5382\/files\/product_image_9783540306764_1.jpg?v=1778860980","url":"https:\/\/www.momoxbooks.com\/products\/jin-yaochu-multi-objective-machine-learning-9783540306764","provider":"momoxbooks","version":"1.0","type":"link"}