Embedded heterogeneous feature selection for conjoint analysis: A SVM approach using L1 penalty.
Sebastián MaldonadoRicardo MontoyaJulio LópezPublished in: Appl. Intell. (2017)
Keyphrases
- feature selection
- support vector
- support vector machine
- support vector machine svm
- multi class
- small sample
- text classification
- machine learning
- text categorization
- selected features
- knn
- feature space
- mutual information
- feature ranking
- feature selection algorithms
- bayes classifier
- svm rfe
- objective function
- classification accuracy
- information gain
- feature weighting
- model selection
- high dimensionality
- hyperplane
- irrelevant features
- generalization ability
- embedded systems
- feature subset
- classification performances
- method for feature selection
- naive bayes
- feature extraction
- high dimension
- svm classification
- input features
- fold cross validation
- dimensionality reduction
- support vectors
- gene selection
- classification models
- text classifiers
- selection criterion
- feature set
- training data
- support vector regression
- multi attribute
- microarray data
- recursive feature elimination
- svm classifier
- logistic regression