Discernibility matrix based incremental feature selection on fused decision tables.
Ye LiuLidi ZhengYeliang XiuHong YinSuyun ZhaoXizhao WangHong ChenCuiping LiPublished in: Int. J. Approx. Reason. (2020)
Keyphrases
- decision table
- discernibility matrix
- feature selection
- feature ranking
- rough set theory
- attribute reduction
- variable precision
- decision rules
- knowledge reduction
- attribute reduction algorithm
- rough sets
- decision trees
- text categorization
- information entropy
- rough set model
- support vector
- feature space
- feature extraction
- feature set
- dominance relation
- machine learning
- feature subset
- feature selection algorithms
- attribute values
- naive bayes
- model selection
- dimensionality reduction
- feature subset selection
- algorithm for attribute reduction
- classification error
- high dimensionality
- support vector machine
- classification accuracy
- pattern recognition
- classification models
- microarray data
- supervised learning
- knowledge discovery
- real world
- neural network