CSU-Carig
Data mining algorithms : explained using R /
by Cichosz, Pawel,
Physical details: 683 pages ; illustration ; ISBN: 9781118332580.
Subject(s):
Data mining.
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Computer algorithms.
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R (Computer program language)
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MATHEMATICS / Probability & Statistics / General.
Online resources:
| Item type | Location | Collection | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|
Electronic Books
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E-Resource Section | E-Books | 006.312 (Browse shelf) | Available |
Part I. Preliminaries -- 1. Tasks -- 2. Basic statistics -- Part II. Classification -- 3. Decision trees -- 4. Naèive Bayes classifier -- 5. Linear classification -- 6. Misclassification costs -- 7. Classification model evaluation -- Part III. Regression -- 8. Linear regression -- 9. Regression trees -- 10. Regression model evaluation -- Part IV. Clustering -- 11. (Dis)similarity measures -- 12. k-Centers clustering -- 13. Hierarchical clustering -- 14. Clustering model evaluation -- Part V. Getting better models -- 15. Model ensembles -- 16. Kernel methods -- 17. Attribute transformation -- 18. Discretization -- 19. Attribute selection.
"This book narrows down the scope of data mining by adopting a heavily modeling-oriented perspective"--
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