New Advances in Machine Learning (E-Book) Yagang Zhang

By: Yagang ZhangPublisher: India In-Teh © 2010Description: viii,366pSubject(s): (E-Book)
Contents:
Introduction to Machine Learning (Page-1) Machine Learning Overview (Page-9) Types of Machine Learning Algorithms (Page19) Methods for Pattern Classification (Page-49) Classification of support vector machine and regression algorithm (Page-75 ) Machine Learning for Multi-stage Selection of Numerical Methods (Page-117) Hierarchical Reinforcement Learning Using a Modular Fuzzy Model for Multi-Agent Problem (Page-137) Toshihiko Watanabe Random Forest-LNS Architecture and Vision (Page-151) Colony Optimization (Page-209) Mahalanobis Support Vector Machines Made Fast and Robust (Page-227) Dynamic Visual Motion Estimation (Page-283) Concept Mining and Inner Relationship Discovery from Text (Page-305) Cognitive Learning for Sentence Understanding (Page-329) A Novel Credit Assignment to a Rule with Probabilistic State Transition (Page-357)
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Item type Current location Home library Collection Call number URL Status Date due Barcode Item holds
Book Book Military College of Signals (MCS)
Military College of Signals (MCS)
NFIC Link to resource Available MCSEB-1553
Total holds: 0

Introduction to Machine Learning (Page-1) Machine Learning Overview (Page-9) Types of Machine Learning Algorithms (Page19) Methods for Pattern Classification (Page-49) Classification of support vector machine and regression algorithm (Page-75 ) Machine Learning for Multi-stage Selection of Numerical Methods (Page-117) Hierarchical Reinforcement Learning Using a Modular Fuzzy Model for Multi-Agent Problem (Page-137) Toshihiko Watanabe Random Forest-LNS Architecture and Vision (Page-151) Colony Optimization (Page-209) Mahalanobis Support Vector Machines Made Fast and Robust (Page-227) Dynamic Visual Motion Estimation (Page-283) Concept Mining and Inner Relationship Discovery from Text (Page-305) Cognitive Learning for Sentence Understanding (Page-329) A Novel Credit Assignment to a Rule with Probabilistic State Transition (Page-357)

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