| Autor: |
Dey, Pallab Kumar, Mukhopadhyay, Sripati |
| Předmět: |
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| Zdroj: |
International Journal of Intelligent Engineering & Systems; 2017, Vol. 10 Issue 5, p19-28, 10p |
| Abstrakt: |
Most of the data mining algorithm's application hampers due to missing attribute values. Inadequate treatment of missing values seriously affects the data mining and classification accuracy. A useful technique has been proposed to deal with missing attribute values. Rough set approach to incomplete information system has been shown. Application of discernible matrix for incomplete information to compute core and reduct has been shown. Imputation based preprocessing approach depends on relation between present attribute value and incomplete attribute value, so have to found most similar object to impute missing value. To find similar objet importance or priority should be given in core attributes, after that reduct attributes if matching occur in corresponding attributes value and other attributes may be neglected. In this paper this concept of core and reduct attributes of rough set has been utilized to fill missing values using the proposed Core Reduct Based (CRB) algorithm. Efficiency of the CRB algorithm in the completeness analysis to incomplete data has been shown by comparing its performance with other existing algorithms using some real life data sets. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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