Feature Selection for Multi-Label Learning Based on F-Neighborhood Rough Sets.
Zhixuan DengZhonglong ZhengDayong DengTianxiang WangYiran HeDawei ZhangPublished in: IEEE Access (2020)
Keyphrases
- rough sets
- multi label learning
- feature selection
- multi label
- rough set theory
- text categorization
- fuzzy sets
- label propagation
- decision rules
- labeled data
- granular computing
- data mining
- semi supervised
- text classification
- rough sets theory
- rule extraction
- unlabeled data
- feature set
- data analysis
- machine learning
- scene classification
- semi supervised learning
- support vector
- pattern recognition
- dimensionality reduction
- decision trees
- training data
- ensemble learning
- classification accuracy
- k nearest neighbor
- naive bayes
- feature space
- support vector machine
- fuzzy logic
- genetic algorithm
- data sets
- real world