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List of machine learning concepts : ウィキペディア英語版 | List of machine learning concepts
==Supervised learning==
* AODE * Artificial neural network * * Backpropagation * * Autoencoders * * Hopfield networks * * Boltzmann machines * * Restricted Boltzmann Machines * * Spiking neural networks * Bayesian statistics * * Bayesian network * * Bayesian knowledge base * Case-based reasoning * Gaussian process regression * Gene expression programming * Group method of data handling (GMDH) * Inductive logic programming * Instance-based learning * Lazy learning * Learning Automata * Learning Vector Quantization * Logistic Model Tree * Minimum message length (decision trees, decision graphs, etc.) * * Nearest Neighbor Algorithm * * Analogical modeling * Probably approximately correct learning (PAC) learning * Ripple down rules, a knowledge acquisition methodology * Symbolic machine learning algorithms * Support vector machines * Random Forests * Ensembles of classifiers * * Bootstrap aggregating (bagging) * * Boosting (meta-algorithm) * Ordinal classification * Information fuzzy networks (IFN) * Conditional Random Field * ANOVA * Linear classifiers * * Fisher's linear discriminant * * Logistic regression * * Multinomial logistic regression * * Naive Bayes classifier * * Perceptron * * Support vector machines * Quadratic classifiers * k-nearest neighbor * Boosting * Decision trees * * C4.5 * * Random forests * * ID3 * * CART * * SLIQ * * SPRINT * Bayesian networks * * Naive Bayes * Hidden Markov models
抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)』 ■ウィキペディアで「List of machine learning concepts」の詳細全文を読む
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