Uncertainty of the Classification Result from a Linear Discriminant Analysis.
Yuhui LuoPublished in: MetroInd4.0&IoT (2020)
Keyphrases
- linear discriminant analysis
- support vector machine svm
- small sample size
- feature extraction
- discriminant analysis
- discriminant features
- dimension reduction
- support vector
- class separability
- fisher criterion
- class discrimination
- feature space
- face recognition
- dimensionality reduction
- discriminative information
- principal component analysis
- principal components analysis
- pattern recognition
- kernel discriminant analysis
- subspace analysis
- null space
- high dimensional data
- dealing with high dimensional data
- classification accuracy
- data mining
- machine learning
- subspace methods
- dimensionality reduction methods
- text classification
- image classification
- support vector machine
- high dimensional
- decision trees
- feature selection
- high dimensionality
- low dimensional
- least squares
- learning algorithm
- sample size
- supervised dimensionality reduction
- pca lda