machine learning algorithms

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 Inductive logic programming Gaussian process regression Gene expression programming Group method of data handling (GMDH) 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