A hybrid approach using rough set theory and hypergraph for feature selection on high-dimensional medical datasets.
M. R. Gauthama RamanNivethitha SomuKrithivasan KannanV. S. Shankar SriramPublished in: Soft Comput. (2019)
Keyphrases
- rough set theory
- high dimensional
- rough sets
- feature selection
- high dimensionality
- attribute reduction
- dimensionality reduction
- feature selection algorithms
- decision table
- feature space
- rule generation
- fuzzy set theory
- decision rules
- knowledge reduction
- granular computing
- rule extraction
- variable precision rough set model
- microarray data
- tool for data mining
- low dimensional
- text categorization
- gene expression data
- rule induction
- data reduction
- fuzzy sets
- data analysis
- model selection
- feature extraction
- information entropy
- equivalence relation
- knowledge discovery
- nearest neighbor
- feature set
- discernibility matrix
- rough sets theory
- high dimensional data
- attribute set
- text classification
- attribute reduction algorithm
- microarray
- concept lattice
- feature subset
- database
- attribute values
- data points
- classification accuracy
- pattern recognition
- decision trees
- machine learning
- data sets