On the fusion of threshold classifiers for categorization and dimensionality reduction.
Hans A. KestlerLudwig LausserWolfgang LindnerGünther PalmPublished in: Comput. Stat. (2011)
Keyphrases
- dimensionality reduction
- feature selection
- classifier fusion
- linear discriminant
- semi supervised dimensionality reduction
- high dimensional data
- classifier combination
- training data
- support vector
- fusion strategies
- low dimensional
- dimensionality reduction methods
- high dimensional
- roc curve
- text categorization
- principal component analysis
- fusion methods
- feature extraction
- linear discriminant analysis
- data representation
- fusion scheme
- pattern recognition
- multiple features
- structure preserving
- decision trees
- manifold learning
- data fusion
- training set
- linear classifiers
- information fusion
- semi supervised
- training samples
- majority voting
- high dimensionality
- principal components
- multi sensor
- image fusion
- classification algorithm
- classifier ensemble
- machine learning algorithms
- individual classifiers
- nonlinear dimensionality reduction
- naive bayes
- pattern recognition and machine learning
- feature space
- ensemble learning
- training examples
- fusion framework
- feature set