395,54 €
439,49 €
-10% with code: EXTRA
Clustering
Clustering
395,54
439,49 €
  • We will send in 10–14 business days.
This is the first book to take a truly comprehensive look at clustering. It begins with an introduction to cluster analysis and goes on to explore: proximity measures; hierarchical clustering; partition clustering; neural network-based clustering; kernel-based clustering; sequential data clustering; large-scale data clustering; data visualization and high-dimensional data clustering; and cluster validation. The authors assume no previous background in clustering and their generous inclusion of…
  • Publisher:
  • ISBN-10: 0470276800
  • ISBN-13: 9780470276808
  • Format: 16.3 x 23.6 x 2.3 cm, hardcover
  • Language: English
  • SAVE -10% with code: EXTRA

Clustering (e-book) (used book) | Don Wunsch | bookbook.eu

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This is the first book to take a truly comprehensive look at clustering. It begins with an introduction to cluster analysis and goes on to explore: proximity measures; hierarchical clustering; partition clustering; neural network-based clustering; kernel-based clustering; sequential data clustering; large-scale data clustering; data visualization and high-dimensional data clustering; and cluster validation. The authors assume no previous background in clustering and their generous inclusion of examples and references help make the subject matter comprehensible for readers of varying levels and backgrounds.

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  • Author: Don Wunsch
  • Publisher:
  • ISBN-10: 0470276800
  • ISBN-13: 9780470276808
  • Format: 16.3 x 23.6 x 2.3 cm, hardcover
  • Language: English English

This is the first book to take a truly comprehensive look at clustering. It begins with an introduction to cluster analysis and goes on to explore: proximity measures; hierarchical clustering; partition clustering; neural network-based clustering; kernel-based clustering; sequential data clustering; large-scale data clustering; data visualization and high-dimensional data clustering; and cluster validation. The authors assume no previous background in clustering and their generous inclusion of examples and references help make the subject matter comprehensible for readers of varying levels and backgrounds.

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