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Mathematical Tools for Data Mining
ISBN-13:
9781447164074
Veröffentl:
2014
Seiten:
831
Autor:
Dan A. Simovici
Serie:
Advanced Information and Knowledge Processing
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
1 - PDF Watermark
Sprache:
Englisch
Beschreibung:
Data mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book. Topics include partially ordered sets, combinatorics, general topology, metric spaces, linear spaces, graph theory. To motivate the reader a significant number of applications of these mathematical tools are included ranging from association rules, clustering algorithms, classification, data constraints, logical data analysis, etc. The book is intended as a reference for researchers and graduate students.
Sets, Relations and Functions.- Partially Ordered Sets.- Combinatorics.- Topologies and Measures.- Linear Spaces.- Norms and Inner Products.- Spectral Properties of Matrices.- Metric Spaces Topologies and Measures.- Convex Sets and Convex Functions.- Graphs and Matrices.- Lattices and Boolean Algebras.- Applications to Databases and Data Mining.- Frequent Item Sets and Association Rules.- Special Metrics.- Dimensions of Metric Spaces.- Clustering.
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