Feature Selection for Partially Labeled Data Based on Neighborhood Granulation Measures
As an effective feature selection technique, rough set theory plays an important part in machine learning. However, it is only applicable to labeled data. In reality, there are massive partially labeled data in machine learning tasks, such as webpage classification, speech recognition, and text cate...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8664571/ |