VRIFA: a nonlinear SVM visualization tool using nomogram and localized radial basis function (LRBF) kernels.
Ngo Anh VienNguyen Hoang VietTaeChoong ChungHwanjo YuSungchul KimBaek Hwan ChoPublished in: CIKM (2009)
Keyphrases
- visualization tool
- radial basis function
- rbf kernel
- support vector
- support vector machine svm
- rbf network
- rbf neural network
- kernel function
- nonlinear functions
- open source
- support vector machine
- basis functions
- neural network
- kernel svms
- artificial neural networks
- positive definite
- feature space
- sequential minimal optimization
- svm classifier
- data analysis
- kernel methods
- multilayer perceptron
- machine learning
- multi layer perceptron
- reproducing kernel hilbert space
- hidden layer
- generalization ability
- graph kernels
- knn
- orthogonal least squares
- multiple kernel learning
- feature extraction
- genetic algorithm
- ls svm
- feature selection
- case study
- data sets
- cross validation
- loss function
- model selection