Effects of hardware heterogeneity on the performance of SVM Alzheimer's disease classifier.
Ahmed AbdulkadirBénédicte MortametPrashanthi VemuriClifford R. Jack Jr.Gunnar KruegerStefan KlöppelPublished in: NeuroImage (2011)
Keyphrases
- support vector
- svm classifier
- support vector machine
- feature selection
- classification algorithm
- training data
- support vector machine svm
- classification method
- text classifiers
- multi class svm
- feature space
- high classification accuracy
- train a support vector machine
- low cost
- knn
- svm classification
- training set
- fuzzy support vector machine
- decision forest
- input features
- decision boundary
- decision function
- support vectors
- multi class
- histogram intersection kernel
- fold cross validation
- kernel function
- small sample
- early diagnosis
- classifier training
- feature vectors
- naive bayes
- k nearest neighbor
- training process
- naive bayes classifier
- text classification
- binary classification
- machine learning
- learning algorithm
- decision trees
- bayesian classifiers
- classification accuracy
- real time
- feature ranking
- multiple kernel learning
- training examples
- logistic regression
- rule based classifier
- rbf kernel
- highest accuracy
- sequential forward selection
- standard svm
- ensemble classifier
- feature maps
- multi class classification
- computer aided diagnosis
- training dataset
- ensemble learning
- feature set
- supervised learning