Dealing with heterogeneity in the context of distributed feature selection for classification.
José Luis Morillo-SalasVerónica Bolón-CanedoAmparo Alonso-BetanzosPublished in: Knowl. Inf. Syst. (2021)
Keyphrases
- feature selection
- classification accuracy
- support vector
- classification models
- text classification
- machine learning
- feature extraction
- feature space
- pattern recognition
- support vector machine
- discriminative features
- feature selection algorithms
- contextual information
- support vector machine svm
- mutual information
- multi agent
- model selection
- automatic classification
- classification algorithm
- feature selection and classification
- wrapper feature selection
- data pre processing
- method for feature selection
- decision trees
- unsupervised learning
- high dimensionality
- bayes classifier
- neural network
- classification performances
- distributed systems
- accurate classification
- small sample
- feature subset selection
- image classification
- ensemble classifier
- class imbalance
- dimension reduction
- distributed environment
- context aware
- web page classification
- unsupervised feature selection
- class separability
- class labels
- global knowledge
- feature subset
- training set
- irrelevant attributes