KSUFS: A Novel Unsupervised Feature Selection Method Based on Statistical Tests for Standard and Big Data Problems
The typical inaccuracy of data gathering and preparation procedures makes erroneous and unnecessary information to be a common issue in real-world applications. In this context, feature selection methods are used in order to reduce the harmful impact of such information in data analysis by removing...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8768389/ |