description Encyclopedia of Machine Learning and Data Mining Overview
The Encyclopedia of Machine Learning and Data Mining is a comprehensive academic reference work published by Springer, edited by Claude Sammut and Geoffrey I. Webb. It serves as an extensive guide to the concepts, algorithms, and applications within the fields of machine learning and data mining. The encyclopedia contains contributions from numerous international experts, providing detailed entries on both foundational theories and emerging techniques in computational intelligence.
It is designed for researchers, students, and practitioners seeking authoritative summaries of specialized topics in computer science.
help Encyclopedia of Machine Learning and Data Mining FAQ
Who edited the Encyclopedia of Machine Learning and Data Mining?
This comprehensive reference work was edited by Claude Sammut and Geoffrey I. Webb. It was published by Springer and serves as a massive expansion of the 2011 Encyclopedia of Machine Learning.
What is the difference between the 2011 version and the newer Encyclopedia of Machine Learning and Data Mining?
The newer edition incorporates the rapidly evolving field of data mining alongside traditional machine learning concepts. It includes hundreds of new entries authored by leading computer scientists and researchers.
What topics does this Springer encyclopedia cover?
It spans the entire spectrum of predictive modeling, artificial intelligence, and statistical data mining. Entries cover everything from basic supervised learning algorithms to advanced deep learning architectures.
Who publishes the Encyclopedia of Machine Learning and Data Mining?
The reference set is published by Springer, a major academic publishing house. It is part of their extensive catalog of computer science and engineering reference texts.
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