Data Mining Techniques Book Information:

< strong> 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 itemset counting, fp-tree growth, sliq, sprint, boat, cart, rainforest, 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 br>Chapter on data warehousing concepts was thoroughly revised to include multidimensional data modelling and Cube computation. The discussion on genetic algorithms was also expanded as a separate br>Chapter in the fourth edition, a br>Chapter on Roc curve for visualizing the performance of a binary classifier and the method for computing auc and its uses has been included.
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• Book Type/Genre :

Business Finance

• Book Binding :

Paperback

• Language :

• Number of Pages :

Page count varies on each edition/reprint

• ISBN - 10 :

• Data Mining Techniques Published On :

• Resource:

Higher Education Textbooks, Business Finance Book is recommended for Students, Teachers, Graduates, Professionals, and all bibliophiles

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