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Mathematical Tools for Data Mining

Mathematical Tools for Data Mining

          
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About the Book

This book integrates the mathematics of data mining with its applications, offering the reader a reference to the mathematical tools required for data mining. Dedicated to the study of set-theoretical foundations of data mining, this book is focused on set theory and several closely related areas: partially ordered sets and lattice theory, metric spaces and combinatorics. The book is structured into 4 parts and presents a comprehensive discussion of the subject. Features and topics include: - Study of functions and relations, - Applications are provided throughout, - Presents graphs and hypergraphs, - Covers partially ordered sets, lattices and Boolean algebras, - Finite partially ordered sets, - Focuses on metric spaces, - Includes combinatorics, - Discusses the theory of the Vapnik-Chervonenkis dimension of collections of sets. Intended as a reference for the working data miner and researchers, a good knowledge of calculus is required to make the best use of this book, which will prove a useful reference.

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.


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Product Details
  • ISBN-13: 9781848002005
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Height: 230 mm
  • No of Pages: 616
  • Series Title: English
  • Weight: 1053 gr
  • ISBN-10: 1848002009
  • Publisher Date: 08 Nov 2018
  • Binding: Hardback
  • Language: English
  • Returnable: N
  • Spine Width: 35 mm
  • Width: 154 mm


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