Mohlo by se vám také líbit

Více informací o knize Multi-Objective Machine Learning

• Parametry knihy
• Anotace
• Oblíbené z jiného soudku

Nákupem získáte 471 bodů

Anotace knihy

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.

Parametry knihy

Zařazení knihy Knihy v angličtině Mathematics & science Physics Statistical physics

• Plný název: Multi-Objective Machine Learning
• Autor: Yaochu Jin
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 660
• EAN: 9783642067969
• ISBN: 3642067964
• ID: 01652002
• Nakladatelství: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
• Hmotnost: 1021 g
• Rozměry: 235 × 155 × 34 mm
• Datum vydání: 22. November 2010

Oblíbené z jiného soudku

---

---

---