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Grouping Multidimensional Data : Recent Advances in Clustering • Kogan, Nicholas

Description: Grouping Multidimensional Data Recent Advances in Clusteringby Jacob Kogan, Charles Nicholas, Marc Teboulle ISBN-13: 9783540283485 ISBN-10: 354028348X Publisher: Springer Binding: Hardcover Publication Year: 2006 Condition: Very Good – clean pages About: refer to image(s) Contents: The Star Clustering Algorithm for Information Organization A Survey of Clustering Data Mining Techniques Similarity-Based Text Clustering: A Comparative Study Clustering Very Large Data Sets with Principal Direction Divisive Partitioning Clustering with Entropy-Like k-Means Algorithms Sampling Methods for Building Initial Partitions TMG: A MATLAB Toolbox for Generating Term-Document Matrices from Text Collections Criterion Functions for Clustering on High-Dimensional Data mySku 6284

Price: 33 USD

Location: Des Moines, Iowa

End Time: 2024-11-04T19:48:37.000Z

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Grouping Multidimensional Data : Recent Advances in Clustering • Kogan, NicholasGrouping Multidimensional Data : Recent Advances in Clustering • Kogan, NicholasGrouping Multidimensional Data : Recent Advances in Clustering • Kogan, Nicholas

Item Specifics

All returns accepted: ReturnsNotAccepted

Subject Area: Computer Vision & Pattern Recognition, Data Processing, Storage & Retrieval, Cluster analysis, Data Mining, database

Publication Name: Grouping Multidimensional Data : Recent Advances in Clustering

Publisher: Springer Berlin / Heidelberg

Subject: Mathematics, Computers, Probability & Statistics

Publication Year: 2005

Type: Textbook

Format: Hardcover

Language: English

Author: Charles Nicholas, Jacob Kogan, Marc Teboulle

Educational Level: Adult & Further Education

Level: Scholarly & Professional

Country/Region of Manufacture: Netherlands

Number of Pages: 268 Pages

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