Книга: Machine Learning: Artificial Neural Network, Supervised Learning, Hidden Markov Model, Support Vector Machine, Inductive Logic Programming

Purchase includes free access to book updates online and a free trial membership in the publisher's book club where you can select from more than a million books without charge. Chapters: Artificial Neural Network, Supervised Learning, Hidden Markov Model, Support Vector Machine, Inductive Logic Programming, Pattern Recognition, Reinforcement Learning, Principal Component Analysis, Self-Organizing Map, Overfitting, Kernel Trick, Granular Computing, Rough Set, Cluster Analysis, Radial Basis Function Network, Perceptron, Concept Learning, Category Utility, Expectation-Maximization Algorithm, Neural Modeling Fields, Dominance-Based Rough Set Approach, Forward-Backward Algorithm, Principle of Maximum Entropy, Nonlinear Dimensionality Reduction, Viterbi Algorithm, Structure Mapping Engine, Non-Negative Matrix Factorization, Learning to Rank, Cross-Validation, Algorithmic Inference, Concept Drift, Activity Recognition, Mixture Model, Formal Concept Analysis, Exponential Mechanism, Information Bottleneck Method, K-Means Clustering, Nearest Neighbor Search, Evolutionary Algorithm, General Architecture for Text Engineering, Markov Decision Process, Conceptual Clustering, Uniform Convergence, Hierarchical Temporal Memory, Simultaneous Localization and Mapping, K-Nearest Neighbor Algorithm, Learning With Errors, Binary Classification, Weka, Group Method of Data Handling, Feature Selection, Analogical Modeling, Learning Classifier System, Multi-Armed Bandit, Iris Flower Data Set, Bregman Divergence, Temporal Difference Learning, Partially Observable Markov Decision Process, Random Forest, Dbscan, Gittins Index, Alternating Decision Tree, Loss Function, Kernel Principal Component Analysis, K-Means++, Explanation-Based Learning, Jabberwacky, K-Medoids, Variable-Order Markov Model, Goldengem, Grammar Induction, Optics Algorithm, Conditional Random Field, Cross-Entropy Method, Structured Svm, Transduction, Co-Training, Backpropagation, Dimens... More: booksllc.net/?id=21523