Classification of Diabetics with Various Degrees of Autonomic Neuropathy Based on Linear and Nonlinear Features Using Support Vector Machine.
Chuang-Chien ChiuShoou-Jeng YehTai-Yue LiPublished in: ICMB (2010)
Keyphrases
- support vector machine
- svm classifier
- feature vectors
- classification method
- feature space
- svm classification
- classification accuracy
- feature extraction
- feature set
- support vector
- support vector machine classifiers
- pattern recognition
- multi class
- input features
- training set
- classification process
- support vector machine svm
- classification algorithm
- feature selection
- classification models
- feature analysis
- feature reduction
- feature values
- machine learning
- high classification accuracy
- extracting features
- image classification
- extracted features
- class labels
- classification performances
- decision forest
- decision boundary
- cost sensitive
- benchmark datasets
- machine learning algorithms
- high dimensionality
- feature representation
- training data
- single feature
- features extraction
- kernel function
- image features
- false positives
- weak classifiers
- selected features
- hyperplane
- discriminative features
- feature ranking
- decision trees
- eeg signals
- text classification
- structured output