-Gaussian Radial Basis Functions for Improving Prediction Accuracy of Gene Classification Using Feature Selection.
Francisco Fernández-NavarroCésar Hervás-MartínezPedro Antonio GutiérrezRoberto RuizJosé C. RiquelmePublished in: ICANN (1) (2010)
Keyphrases
- prediction accuracy
- feature selection
- radial basis function
- support vector
- predictive accuracy
- support vector machine svm
- classification accuracy
- support vector machine
- generalization capabilities
- machine learning
- predictive power
- feature extraction
- text classification
- ensemble methods
- microarray datasets
- feature set
- pattern recognition
- radial basis function neural network
- improve the prediction accuracy
- multi layer perceptron
- high dimensionality
- rbf network
- feature space
- gene expression data
- knn
- pattern classification
- feature ranking
- function approximation
- multilayer perceptron
- decision trees
- basis functions
- artificial neural networks
- gene selection
- activation function
- web page prediction
- neural network
- orthogonal least squares
- feature subset
- microarray data
- machine learning methods
- microarray
- svm classifier
- machine learning algorithms
- text categorization
- k nearest neighbor
- small number
- feature vectors
- pairwise
- training set
- computer vision
- genetic algorithm