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Encyclopedia of Machine Learning [electronic resource] / edited by Claude Sammut, Geoffrey I. Webb.

By: Sammut, Claude [editor.].
Contributor(s): Webb, Geoffrey I [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Boston, MA : Springer US, 2010Description: XXVI, 1031p. 95 illus. in color. eReference. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9780387301648.Subject(s): Computer science | Data mining | Electronic data processing | Artificial intelligence | Optical pattern recognition | Computer Science | Artificial Intelligence (incl. Robotics) | Computing Methodologies | Data Mining and Knowledge Discovery | Pattern Recognition | Statistics for Engineering, Physics, Computer Science, Chemistry and Earth SciencesDDC classification: 006.3 Online resources: Click here to access online
Contents:
Clustering -- Statistical Machine Learning -- Statistical Language Learning -- Inductive Logic Programming -- Learning and Logic -- Meta-Learning -- ROC analysis -- Information Theory -- Instance-based Learning Time Series -- Policy Search and Active Selection -- Reinforcement Learning -- Artificial Neural Network -- Text Mining -- Machine Learning in Bioinformatics -- Rule Learning -- Evolutionary Computation -- Behavioral Cloning -- Search -- Computational Learning Theory -- Online Learning -- Learning Paradigms -- Model-based Reinforcement Learning -- Active Learning -- Explanation-based Learning -- Data Mining -- Graph Mining.
In: Springer eBooks
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Clustering -- Statistical Machine Learning -- Statistical Language Learning -- Inductive Logic Programming -- Learning and Logic -- Meta-Learning -- ROC analysis -- Information Theory -- Instance-based Learning Time Series -- Policy Search and Active Selection -- Reinforcement Learning -- Artificial Neural Network -- Text Mining -- Machine Learning in Bioinformatics -- Rule Learning -- Evolutionary Computation -- Behavioral Cloning -- Search -- Computational Learning Theory -- Online Learning -- Learning Paradigms -- Model-based Reinforcement Learning -- Active Learning -- Explanation-based Learning -- Data Mining -- Graph Mining.

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