Linear Discriminant Analysis Tumour Classification for Unsupervised Segmented Mammographies.
Cristiana Moroz-DubencoAnca AndreicaPublished in: KES (2023)
Keyphrases
- linear discriminant analysis
- discriminant features
- small sample size
- discriminant analysis
- feature extraction
- support vector machine svm
- dimension reduction
- support vector
- feature space
- face recognition
- fisher criterion
- discriminative information
- discriminant projection
- dimensionality reduction
- principal component analysis
- class separability
- class discrimination
- principal components analysis
- pattern recognition
- classification accuracy
- high dimensional data
- unsupervised learning
- locality preserving projections
- subspace analysis
- kernel discriminant analysis
- decision trees
- subspace methods
- null space
- linear discriminant
- supervised dimensionality reduction
- supervised learning
- feature vectors
- training set
- involving high dimensional data
- semi supervised
- pca lda
- machine learning
- unsupervised feature selection
- scatter matrix
- svm classifier
- dimensionality reduction methods
- high dimensionality
- data sets
- sample size
- training samples
- model selection
- text classification
- feature set
- support vector machine
- neural network