An experimental comparison of Random Projection ensembles with linear kernel SVMs and Bagging and BagBoosting methods for the classification of gene expression data.
Raffaella FolgieriPublished in: WIRN (2009)
Keyphrases
- gene expression data
- decision trees
- kernel svms
- machine learning methods
- random projections
- machine learning
- ensemble methods
- high dimensionality
- gene expression
- machine learning algorithms
- classification accuracy
- feature selection
- pattern recognition
- support vector machine svm
- image classification
- text classification
- feature set
- least squares
- feature extraction
- dimension reduction
- support vector machine
- training set
- neural network