L.) for Its Classification by Linear Discriminant Analysis.
Xavier CetóNúria SerranoMiriam AragóAlejandro GámezMiquel EstebanJosé Manuel Díaz-CruzOscar NúñezPublished in: Sensors (2018)
Keyphrases
- linear discriminant analysis
- support vector machine svm
- feature extraction
- discriminant analysis
- dimension reduction
- small sample size
- feature space
- support vector
- discriminant features
- class discrimination
- class separability
- dimensionality reduction
- discriminative information
- fisher criterion
- face recognition
- principal component analysis
- feature vectors
- null space
- feature analysis
- subspace analysis
- classification accuracy
- high dimensional data
- pattern recognition
- principal components analysis
- kernel discriminant analysis
- high dimensionality
- image classification
- decision trees
- feature selection
- text classification
- supervised dimensionality reduction
- subspace methods
- support vector machine
- dealing with high dimensional data
- machine learning
- locality preserving projections
- training samples
- low dimensional
- data sets
- linear discriminant
- principle component analysis
- dimensionality reduction methods
- scatter matrix
- generalized discriminant analysis
- involving high dimensional data