Predictive Clustering

Beschreibung

This book introduces a novel paradigm for machine learning and data mining called predictive clustering, which covers a broad variety of learning tasks and offers a fresh perspective on existing techniques. The book presents an informal introduction to predictive clustering, describing learning tasks and settings, and then continues with a formal description of the paradigm, explaining algorithms for learning predictive clustering trees and predictive clustering rules, as well as presenting the applicability of these learning techniques to a broad range of tasks. Variants of decision tree learning algorithms are also introduced. Finally, the book offers several significant applications in ecology and bio-informatics. The book is written in a straightforward and easy-to-understand manner, aimed at varied readership, ranging from researchers with an interest in machine learning techniques to practitioners of data mining technology in the areas of ecology and bioinformatics.
Features a new data mining approach: predictive clustering trees and rules Presents a higher efficiency of the learning and prediction process Provides straightforward content in an easy-to-understand manner

Autor*in

Hendrik Blockeel

Themen in »Predictive Clustering«

Data mining Machine learning Predictive clustering analysis of remote sensing data bio-informatics classification clustering clustering time-series data eco-informatics ecological modeling environmental quality classification gene expression data analysis habitat modeling hierarchical classification learning algorithms

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