Variable selection for noisy data applied in proteomics.
Noura DridiAudrey GiremusJean-François GiovannelliCaroline TruntzerPascal RoyL. GerfautJean-Philippe CharrierPatrick DucoroyCatherine MercierPierre GrangeatPublished in: ICASSP (2014)
Keyphrases
- noisy data
- variable selection
- high dimensional
- input variables
- cross validation
- missing data
- stochastic search
- naive bayes classifier
- high dimensionality
- neural network
- missing values
- high dimensional data
- input data
- model selection
- fuzzy logic
- similarity measure
- feature selection
- linear models
- machine learning
- noise free
- data sets
- group lasso