Using Discriminative Dimensionality Reduction to Visualize Classifiers.
Alexander SchulzAndrej GisbrechtBarbara HammerPublished in: Neural Process. Lett. (2015)
Keyphrases
- dimensionality reduction
- feature selection
- semi supervised dimensionality reduction
- feature extraction
- linear discriminant
- unsupervised learning
- semi supervised
- discriminative classifiers
- low dimensional
- linear classifiers
- class discrimination
- dimensionality reduction methods
- high dimensional
- bayesian network classifiers
- data representation
- principal component analysis
- high dimensionality
- data points
- lower dimensional
- high dimensional data
- latent space
- decision trees
- object category recognition
- naive bayes
- pattern recognition
- manifold learning
- support vector
- principal components
- dimension reduction
- classification algorithm
- svm classifier
- linear discriminant analysis
- test set
- highly discriminative
- machine learning algorithms
- ensemble classifier
- classifier training
- support vector machine
- pairwise
- training set
- decision stumps
- pattern recognition and machine learning
- discriminative information
- machine learning
- discriminative learning
- subspace learning
- feature space
- visualization tool
- metric learning
- feature subset
- discriminant analysis
- training samples
- feature set
- multi class