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Multi-Objective Machine Learning

by Yaochu Jin
Save 35% Save 35%
Current price ₹13,942.00
Original price ₹21,449.00
Original price ₹21,449.00
Original price ₹21,449.00
(-35%)
₹13,942.00
Current price ₹13,942.00

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Book cover type: Paperback
  • ISBN13: 9783642067969
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Publication Date:
  • Pages: 660
  • Original Price: EUR 199.99
  • Language: English
  • Edition: N/A
  • Item Weight: 1004 grams
  • BISAC Subject(s): Applied, Artificial Intelligence / General, and Physics / Mathematical & Computational

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.

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