Data Mining Techniques - Couverture souple

Name: Data Mining Techniques
Author: Pujari, Arun K.
ISBN: 9789386235053

Pujari, Arun K.

Couverture souple

ISBN 10 : 9386235056 ISBN 13 : 9789386235053

Editeur : Universities Press, 2016

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�diteur: Universities Press
Date d'�dition: 2016
Langue: anglais
ISBN 10: 9386235056
ISBN 13: 9789386235053
Reliure: Broch�
Nombre de pages: 423
Coordonn�es du fabricant: non disponible
Personne responsable: non disponible

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Data Mining Techniques 4Th Edition

Arun K Pujari

Edit� par Universities Press, 2016

ISBN 10 : 9386235056 ISBN 13 : 9789386235053

Neuf Soft cover

Vendeur : Shalimar Books, London, Royaume-Uni

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Soft cover. Etat : New. N� de r�f. du vendeur IND-9789386235053

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Data Mining Techniques

Arun K Pujari

Edit� par Universities Press, 2016

ISBN 10 : 9386235056 ISBN 13 : 9789386235053

Neuf Soft cover

Vendeur : Vedams eBooks (P) Ltd, New Delhi, Inde

�valuation du vendeur 4 sur 5 �toiles

Soft cover. Etat : New. 4th Edition. Contents: Foreword. Preface. 1. Introduction. 2. Data warehousing. 3. Data mining. 4. Association rules. 5. Clustering techniques. 6. Decision trees. 7. Rough set theory. 8. Genetic algorithm. 9. Other techniques. 10. Performance evaluation - ROC curve. 11. Web mining. 12. Temporal and spatial data mining. Index. This book addresses all the major and latest techniques of data mining. It deals in detail with the algorithms for discovering association rules for clustering and building decision trees, and techniques such as neural networks, genetic algorithms, rough set theory and support vector machine used in data mining. The algorithmic details of different techniques such as Apriori, Pincer-search, Dynamic Item set Counting, FP-Tree growth, SLIQ, SPRINT, BOAT, CART, Rain Forest, BIRCH, CURE, BUBBLE, ROCK, STIRR, PAM, CLARANS, DBSCAN, GSP, SPADE and SPIRIT are covered. The book also discusses the mining of web, spatial, temporal and text data. In the third edition, the chapter on data warehousing concepts was thoroughly revised to include multidimensional data modeling and cube computation. The discussion on genetic algorithms was also expanded as a separate chapter. In the fourth edition, a chapter on ROC curve for visualizing the performance of a binary classifier and the method for computing AUC and its uses has been included. Students of computer science, mathematical science and management will find this introductory textbook beneficial for a first course on the subject; the exposition of concepts with supporting illustrative examples and exercises makes it suitable for self-study as well. N� de r�f. du vendeur 119634

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