Support vector machine and optimal parameter selection for high-dimensional imbalanced data.
Yugo NakayamaPublished in: Commun. Stat. Simul. Comput. (2022)
Keyphrases
- parameter selection
- imbalanced data
- support vector machine
- high dimensional
- svm classifier
- feature space
- decision boundary
- high dimensionality
- ls svm
- feature selection
- data points
- machine learning
- class distribution
- support vector machine svm
- low dimensional
- multi class
- hyperplane
- ensemble methods
- feature vectors
- model selection
- ensemble classifier
- training set
- linear regression
- closed form
- active learning
- training samples
- variable selection
- ensemble learning
- k nearest neighbor
- support vector
- training data
- similarity measure
- dimensionality reduction
- neural network