Mathematical Tools for Data Mining Set Theory, Partial Orders, Combinatorics /

• Main Authors: Simovici, Dan A. (Author), Djeraba, Chabane (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: London : Springer London, 2008.
• Series: Advanced Information and Knowledge Processing
• Subjects: Computer science.; Computer science > Mathematics.; Data mining.; Computer mathematics.; Computer Science.; Data Mining and Knowledge Discovery.; Mathematics of Computing.; Discrete Mathematics in Computer Science.; Computational Mathematics and Numerical Analysis.

The maturing of the field of data mining has brought about an increased level of mathematical sophistication. Such disciplines like topology, combinatorics, partially ordered sets and their associated algebraic structures (lattices and Boolean algebras), and metric spaces are increasingly applied in...

Table of Contents:

• Set Theory
• Sets, Relations, and Functions
• Algebras
• Graphs and Hypergraphs
• Partial Orders
• Partially Ordered Sets
• Lattices and Boolean Algebras
• Topologies and Measures
• Frequent Item Sets and Association Rules
• Applications to Databases and Data Mining
• Rough Sets
• Metric Spaces
• Dissimilarities, Metrics, and Ultrametrics
• Topologies and Measures on Metric Spaces
• Dimensions of Metric Spaces
• Clustering
• Combinatorics
• Combinatorics
• The Vapnik-Chervonenkis Dimension.