[1]TANG Rong,LUO Chuan,CAO Qian,et al.Incremental approach for feature selection in incomplete data while updating feature values[J].CAAI Transactions on Intelligent Systems,2021,16(3):493-501.[doi:10.11992/tis.202006045]
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Incremental approach for feature selection in incomplete data while updating feature values
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
16
Number of periods:
2021 3
Page number:
493-501
Column:
学术论文—知识工程
Public date:
2021-05-05
- Title:
- Incremental approach for feature selection in incomplete data while updating feature values
- Keywords:
- feature selection; dimensional reduction; rough set; information entropy; incomplete data; missing values; heuristic search; incremental learning
- CLC:
- TP18
- DOI:
- 10.11992/tis.202006045
- Abstract:
- In practical application, data often exhibits incomplete and dynamic characteristics. For the feature selection problem in dynamic incomplete data, an incremental feature selection method based on the tolerance rough set model and information entropy theory is proposed. First, the update patterns of conditional partition and decision classification are established based on the variation of feature values in incomplete information systems. The incremental computing mechanism of incomplete tolerance information entropy as the evaluation criterion of feature importance is built subsequently. Such an incremental mechanism is integrated into the iterative calculation of feature importance during the heuristic search of optimal feature subset, and an incremental feature selection algorithm for dynamic variation of feature values is developed. Finally, the effectiveness and efficiency of the proposed incremental algorithm are verified on several standard UCI datasets in terms of classification accuracy, decision performance, and computing efficiency.
- References:
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Last Update:
2021-06-25