Randomized boosting with multivariable base-learners for high-dimensional variable selection and prediction.
Christian StaerkAndreas MayrPublished in: BMC Bioinform. (2021)
Keyphrases
- variable selection
- base learners
- cross validation
- high dimensional
- ensemble methods
- prediction accuracy
- ensemble learning
- model selection
- regression problems
- random forests
- learning scheme
- base classifiers
- meta learning
- cost sensitive
- decision trees
- dimension reduction
- classification algorithm
- generalization ability
- low dimensional
- high dimensional data
- feature selection
- hyperparameters
- training set
- support vector
- learning algorithm
- training data
- learning tasks
- benchmark datasets
- loss function
- random forest
- least squares
- training process
- data points
- pattern recognition
- neural network
- classification models
- text categorization
- training samples
- dimensionality reduction
- multi class
- artificial neural networks
- feature space
- weak classifiers
- data mining