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Clustering [Hardcover]

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  • Category: Books (Computers)
  • Author:  Xu, Rui, Wunsch, Don
  • Author:  Xu, Rui, Wunsch, Don
  • ISBN-10:  0470276800
  • ISBN-10:  0470276800
  • ISBN-13:  9780470276808
  • ISBN-13:  9780470276808
  • Publisher:  Wiley-IEEE Press
  • Publisher:  Wiley-IEEE Press
  • Pages:  368
  • Pages:  368
  • Binding:  Hardcover
  • Binding:  Hardcover
  • Pub Date:  01-May-2008
  • Pub Date:  01-May-2008
  • SKU:  0470276800-11-MPOD
  • SKU:  0470276800-11-MPOD
  • Item ID: 100174770
  • Seller: ShopSpell
  • Ships in: 2 business days
  • Transit time: Up to 5 business days
  • Delivery by: Jan 13 to Jan 15
  • Notes: Brand New Book. Order Now.
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.PREFACE.

1. CLUSTER ANALYSIS.

1.1. Classifi cation and Clustering.

1.2. Defi nition of Clusters.

1.3. Clustering Applications.

1.4. Literature of Clustering Algorithms.

1.5. Outline of the Book.

2. PROXIMITY MEASURES.

2.1. Introduction.

2.2. Feature Types and Measurement Levels.

2.3. Defi nition of Proximity Measures.

2.4. Proximity Measures for Continuous Variables.

2.5. Proximity Measures for Discrete Variables.

2.6. Proximity Measures for Mixed Variables.

2.7. Summary.

3. HIERARCHICAL CLUSTERING.

3.1. Introduction.

3.2. Agglomerative Hierarchical Clustering.

3.3. Divisive Hierarchical Clustering.

3.4. Recent Advances.

3.5. Applications.

3.6. Summary.

4. PARTITIONAL CLUSTERING.

4.1. Introduction.

4.2. Clustering Criteria.

4.3. K-Means Algorithm.

4.4. Mixture DenslÓ/

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