Classification of normal and abnormal samples of peripheral blood by linear mapping of the feature space.
G. H. LandeweerdTeun TimmersEdzard S. GelsemaM. BinsM. R. HaliePublished in: Pattern Recognit. (1983)
Keyphrases
- feature space
- training samples
- training set
- classification accuracy
- feature vectors
- high dimensional feature space
- feature selection
- feature extraction
- high dimensionality
- classification algorithm
- support vector machine
- sample set
- pattern recognition
- linearly separable
- small sample
- dimension reduction
- machine learning
- supervised learning
- feature set
- image classification
- input data
- data sets
- high dimensional
- support vector
- support vector machine svm
- class labels
- pattern classification
- classification method
- decision trees
- discriminant function
- hyperplane
- sample space
- model selection
- mean shift
- text classification
- principal component analysis
- data points
- linear discriminant analysis
- input space
- kernel function
- unsupervised learning
- dimensionality reduction
- training data
- optimum path forest