Efficient feature subset selection model for high dimensional data
نویسندگان
چکیده
منابع مشابه
Feature Subset Selection using Rough Sets for High Dimensional Data
---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Feature Selection (FS) is applied to reduce the number of features in many applications where data has multiple features. FS is an essential step in successful data mining applications, which can effectively reduce data dimensionality by removing t...
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Feature Selection is to selecting the useful features from the original dataset for improve the more accurate results. Constrained Based Feature Subset Selection(CFSS) Algorithm Removes irrelevant and redundant features. This method is to find a similarity computation based on the entropy and conditional entropy values. After computing similarity computation to applied Approximate Relevancy(AR)...
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pathological changes within an organ can be reflected as proteomic patterns in biological fluids such as plasma, serum, and urine. the surface-enhanced laser desorption and ionization time-of-flight mass spectrometry (seldi-tof ms) has been used to generate proteomic profiles from biological fluids. mass spectrometry yields redundant noisy data that the most data points are irrelevant features ...
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ژورنال
عنوان ژورنال: International Journal on Cybernetics & Informatics
سال: 2016
ISSN: 2320-8430,2277-548X
DOI: 10.5121/ijci.2016.5217