An Interpretable Semi-supervised Classifier using Rough Sets for Amended Self-labeling.
Isel GrauDipankar SenguptaMaría Matilde García LorenzoAnn NowéPublished in: FUZZ-IEEE (2020)
Keyphrases
- rough sets
- supervised classifiers
- supervised classification
- rough set theory
- fuzzy sets
- data sets
- decision rules
- granular computing
- sentiment analysis
- information entropy
- attribute reduction
- rough sets theory
- active learning
- image segmentation
- training set
- data mining
- unsupervised learning
- semi supervised learning
- tool for data mining
- labeled data
- data analysis
- supervised learning
- pattern recognition
- inductive machine learning
- machine learning
- learning environment
- rough set model
- fuzzy logic
- decision table
- training data
- fuzzy rough sets
- dominance relation
- neural network
- artificial intelligence
- rough approximations
- e learning
- knowledge base
- decision trees
- classification rules