High dimensional classification with combined adaptive sparse PLS and logistic regression.
Ghislain DurifLaurent ModoloJakob MichaelssonJeff E. MoldSophie Lambert-LacroixFranck PicardPublished in: Bioinform. (2018)
Keyphrases
- logistic regression
- generalized linear models
- high dimensional
- decision trees
- support vector
- logistic regression models
- fold cross validation
- naive bayes
- linear support vector machines
- classification accuracy
- classification trees
- chi square
- linear svm
- high dimensionality
- feature space
- credit scoring
- class membership probabilities
- regression model
- text classification
- loss function
- dimension reduction
- training samples
- classification and regression trees
- breast cancer
- logistic model
- support vector machine
- class labels
- belief nets
- odds ratio
- partial least squares
- high dimension
- machine learning
- low dimensional
- image classification
- input space
- svm classifier
- model selection
- knowledge discovery
- feature extraction
- support vector machine svm
- dimensionality reduction
- nearest neighbor
- semi supervised
- feature selection