[PDF.93xm] Uncertainty Modeling for Data Mining: A Label Semantics Approach (Advanced Topics in Science and Technology in China)

Uncertainty Modeling for Data Mining: A Label Semantics Approach (Advanced Topics in Science and Technology in China)

[PDF.gi09] Uncertainty Modeling for Data Mining: A Label Semantics Approach (Advanced Topics in Science and Technology in China)

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 | #6816330 in Books |  2015-02-18 | Original language:English | PDF # 1 |  .90 x6.20 x9.20l,.0 | File type: PDF | 291 pages

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||From the Back Cover|Machine learning and data mining are inseparably connected with uncertainty. The observable data for learning is usually imprecise, incomplete or noisy. Uncertainty Modeling for Data Mining: A Label Semantics Approach introduces 'label

Machine learning and data mining are inseparably connected with uncertainty. The observable data for learning is usually imprecise, incomplete or noisy. Uncertainty Modeling for Data Mining: A Label Semantics Approach introduces 'label semantics', a fuzzy-logic-based theory for modeling uncertainty. Several new data mining algorithms based on label semantics are proposed and tested on real-world datasets. A prototype interpretation of label semantics and new pr...

You easily download any file type for your device.Uncertainty Modeling for Data Mining: A Label Semantics Approach (Advanced Topics in Science and Technology in China)   |  Zengchang Qin, Yongchuan Tang. I have read it a couple of times and even shared with my family members. Really good. Couldnt put it down.

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