Can I read Multi-Objective Machine Learning (Studies in Computational Intelligence) (Studies in Computational Intelligence) on EtoBox?

Multi-Objective Machine Learning (Studies in Computational Intelligence) (Studies in Computational Intelligence) by Yaochu Jin (ed.) is a nonfiction available to read on EtoBox.

What is Multi-Objective Machine Learning (Studies in Computational Intelligence) (Studies in Computational Intelligence) about?

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.

Who reads Multi-Objective Machine Learning (Studies in Computational Intelligence) (Studies in Computational Intelligence)?

Author

Yaochu Jin (ed.)

Publisher

Springer Science & Business Media

Published

2006

Language

EN

ISBN

9783540330196

Category

nonfiction

Subjects

Science, Music, Engineering