Mathematical Methods for Knowledge Discovery and Data Mining

Description

The field of data mining has seen a demand in recent years for the development of ideas and results in an integrated structure. Mathematical Methods for Knowledge Discovery & Data Mining focuses on the mathematical models and methods that support most data mining applications and solution techniques, covering such topics as association rules; Bayesian methods; data visualization; kernel methods; neural networks; text, speech, and image recognition; and many others. This Premier Reference Source is an invaluable resource for scholars and practitioners in the fields of biomedicine, engineering, finance and insurance, manufacturing, marketing, performance measurement, and telecommunications.

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1. Ebooks list page : 1431
2. Mathematical Methods for Knowledge Discovery and Data Mining
3. Mathematical Methods for Knowledge Discovery and Data Mining
4. Data Mining: Knowledge Discovery Methods
5. Data Mining: Knowledge Discovery Methods
6. Multimedia Data Mining (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
7. Data Mining and Knowledge Discovery Technologies (Advances in Data Warehousing and Mining)
8. Statistical Data Mining & Knowledge Discovery
9. Advances in Knowledge Discovery and Data Mining
10. Data Mining: A Knowledge Discovery Approach
11. Multimedia Data Mining and Knowledge Discovery
12. Data Mining and Knowledge Discovery Technologies
13. Geographic Data Mining and Knowledge Discovery, Second Edition
14. Introduction to Data Mining and Knowledge Discovery, Third Edition
15. Soft Computing for Knowledge Discovery and Data Mining
16. Knowledge Discovery and Data Mining: Challenges and Realities