On the role of feature space granulation in feature selection processes.
Marek GrzegorowskiAndrzej JanuszDominik SlezakMarcin S. SzczukaPublished in: IEEE BigData (2017)
Keyphrases
- feature space
- feature selection
- high dimensionality
- dimensionality reduction
- classification accuracy
- feature vectors
- high dimensional
- feature set
- rough sets
- feature subset
- mean shift
- dimension reduction
- cognitive process
- image representation
- support vector machine
- mutual information
- kernel function
- process model
- text classification
- input data
- low dimensional
- data sets
- class separability
- machine learning
- principal component analysis
- feature extraction
- kernel methods
- high dimension
- dissimilarity measure
- irrelevant features
- hyperplane
- input space
- fuzzy model
- computational models
- image retrieval
- text categorization
- data points
- model selection
- multi class
- fuzzy logic
- discriminatory power
- method for feature selection
- unsupervised feature selection
- kernel pca
- granular computing
- multi task
- fuzzy sets
- knn
- training set
- support vector
- neural network