Encyclopedia of Machine Learning and Data Mining - Sammut, Claude; Webb, Geoffrey I.; SpringerLink (Online service) (New York, NY : Springer US : Imprint: Springer, 2017)
Abduction -- Adaptive Resonance Theory -- Anomaly Detection -- Bayes Rule -- Case-Based Reasoning -- Categorical Data Clustering -- Causality -- Clustering from Data Streams -- Complexity in Adaptive Systems -- Complexity of Inductive Inference -- Computational Complexity of Learning -- Confusion Matrix -- Connections Between Inductive Inference and Machine Learning -- Covariance Matrix -- Decision List -- Decision Lists and Decision Trees -- Decision Tree -- Deep Learning -- Density-Based Clustering -- Dimensionality Reduction -- Document Classification -- Dynamic Memory Model -- Empirical Risk Minimization -- Error Rate -- Event Extraction from Media Texts -- Evolutionary Clustering -- Evolutionary Computation in Economics -- Evolutionary Computation in Finance -- Evolutionary Computational Techniques in Marketing -- Evolutionary Feature Selection and Construction -- Evolutionary Kernel Learning -- Evolutionary Robotics -- Expectation Maximization Clustering -- Expectation Propagation -- Feature Construction in Text Mining -- Feature Selection -- Feature Selection in Text Mining -- Gaussian Distribution -- Gaussian Process -- Generative and Discriminative Learning -- Grammatical Inference -- Graphical Models -- Hidden Markov Models -- Inductive Inference -- Inductive Logic Programming -- Inductive Programming -- Inductive Transfer -- Inverse Reinforcement Learning -- Kernel Methods -- K-Means Clustering -- K-Medoids Clustering -- K-Way Spectral Clustering -- Learning Algorithm Evaluation -- Learning Graphical Models -- Learning Models of Biological Sequences -- Learning to Rank -- Learning Using Privileged Information -- Linear Discriminant -- Linear Regression -- Locally Weighted Regression for Control -- Machine Learning and Game Playing -- Manhattan Distance -- Maximum Entropy Models for Natural Language Processing -- Mean Shift -- Metalearning -- Minimum Description Length Principle -- Minimum Message Length -- Mixture Model -- Model Evaluation -- Model Trees -- Multi Label Learning -- Naïve Bayes -- Occam's Razor -- Online Controlled Experiments and A/B Testing -- Online Learning -- Opinion Stream Mining -- PAC Learning -- Partitional Clustering -- Phase Transitions in Machine Learning.
Keywords: Artificial intelligence; Data mining; Statistics .; Pattern recognition; Artificial Intelligence; Data Mining and Knowledge Discovery; Statistics and Computing/Statistics Programs; Pattern Recognition