Brain Tumor Classification Using Principal Component Analysis and Kernel Support Vector Machine.
Richard Torres-MolinaCarlos Bustamante-OrellanaAndrés Riofrío-ValdiviesoFrancisco Quinga-SocasiRobinson GuachiLorena Guachi-GuachiPublished in: IDEAL (2) (2019)
Keyphrases
- support vector machine
- feature space
- support vector
- principal component analysis
- kernel function
- svm classifier
- kernel principal component analysis
- svm classification
- brain tumors
- feature vectors
- kernel methods
- support vector machine svm
- classification accuracy
- histogram intersection kernel
- classification algorithm
- high classification accuracy
- classification method
- feature selection
- training set
- dimension reduction methods
- decision boundary
- kernel pca
- dimension reduction
- machine learning
- tree kernels
- decision trees
- feature extraction
- string kernels
- feature reduction
- training procedure
- pattern recognition
- kernel machines
- soft margin
- magnetic resonance images
- multi class
- magnetic resonance spectroscopy
- dimensionality reduction
- information processing
- principal components
- mr images
- independent component analysis
- knn