Encyclopedia of Machine Learning and Data Mining

Beschreibung

This authoritative, expanded and updated second edition of Encyclopedia of Machine Learning and Data Mining provides easy access to core information for those seeking entry into any aspect within the broad field of Machine Learning and Data Mining.  A paramount work, its 800 entries - about 150 of them newly updated or added - are filled with valuable literature references, providing the reader with a portal to more detailed information on any given topic.Topics for the Encyclopedia of Machine Learning and Data Mining include Learning and Logic, Data Mining, Applications, Text Mining, Statistical Learning, Reinforcement Learning, Pattern Mining, Graph Mining, Relational Mining, Evolutionary Computation, Information Theory, Behavior Cloning, and many others.  Topics were selected by a distinguished international advisory board. Each peer-reviewed, highly-structured entry includes a definition, key words, an illustration, applications, a bibliography, and links to related literature.The entries are expository and tutorial, making this reference a practical resource for students, academics, or professionals who employ machine learning and data mining methods in their projects. Machine learning and data mining techniques have countless applications, including data science applications, and this reference is essential for anyone seeking quick access to vital information on the topic.

Presents 800 entries covering key concepts and terms in the broad field of machine learning

Updates and informs through in-depth essays and definitions, historical background, key applications, and bibliographies

Supports quick and efficient discovery of information through extensive cross-references

Opens the field to those inquiring into this fast-growing area of research

Includes supplementary material: sn.pub/extras

Autor*in

Claude Sammut

Themen in »Encyclopedia of Machine Learning and Data Mining«

Active learning big data clustering computational learning theory data mining data visualisation graph mining inductive logic programming information theory machine learning in bioinformatics meta-learning mining social data online learning pattern discovery recommender systems

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“The topics covered in the revised edition include applications, data mining, evolutionary computation, graph mining, information theory, learning and logic, pattern mining, reinforcement learning, relational mining, statistical learning, and text mining. … I recommend the encyclopedia as a valuable resource for libraries … .” (S. V. Nagaraj, Computing Reviews, January, 2018)

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