Integrating spatial-anatomical regularization and structure sparsity into SVM: Improving interpretation of Alzheimer's disease classification.
Zhuo SunYuchuan QiaoBoudewijn P. F. LelieveldtMarius StaringAlzheimer's Disease Neuroimaging InitiativePublished in: NeuroImage (2018)
Keyphrases
- support vector machine svm
- support vector
- support vector machine
- classification algorithm
- classification method
- svm classifier
- feature vectors
- classification accuracy
- svm classification
- feature space
- improves the classification accuracy
- generalization ability
- training set
- machine learning
- pattern recognition
- feature extraction
- decision trees
- medical images
- high classification accuracy
- decision boundary
- multi class classification
- feature selection
- polynomial kernels
- knn
- training data
- spatial information
- class labels
- supervised learning
- support vector machine classifiers
- mixed norm
- maximum margin
- support vectors
- regularization parameter
- kernel methods
- kernel function
- image classification
- high dimensional