Choosing the kernel parameters for support vector machines by the inter-cluster distance in the feature space.
Kuo-Ping WuSheng-De WangPublished in: Pattern Recognit. (2009)
Keyphrases
- kernel parameters
- inter cluster
- kernel function
- support vector
- feature space
- kernel methods
- learning machines
- intra cluster
- support vector machine
- hyperplane
- gaussian processes
- classification accuracy
- feature selection
- arbitrary shape
- kernel machines
- input space
- high dimensional
- feature subset
- support vector regression
- learning problems
- kernel matrix
- cross validation
- loss function
- principal component analysis
- feature vectors
- support vectors
- svm classifier
- training samples
- low dimensional
- dimensionality reduction
- machine learning
- euclidean distance
- distance measure
- feature set
- multiple kernel learning
- data points
- data mining
- training process
- regularization parameter
- probabilistic model
- image segmentation
- image processing