Boosting MMSE Receivers Using AdaBoost.
Onkar DabeerSrinidhi NagarajaA. ChockalingamPublished in: VTC Fall (2013)
Keyphrases
- boosting algorithms
- weak learners
- adaboost algorithm
- weak classifiers
- base classifiers
- strong classifier
- ensemble learning
- ensemble methods
- face detection
- multi class
- learning algorithm
- minimum mean square error
- decision stumps
- weak hypotheses
- cost sensitive
- loss function
- training error
- face detector
- decision tree ensembles
- multi class boosting
- binary classification
- multi class learning
- multipath
- object detection
- multi class classification
- feature selection
- linear classifiers
- base learners
- training process
- ensemble classifier
- majority voting
- decision trees
- random forests
- training samples
- minimum margin
- support vector
- training data
- prediction accuracy
- boosted classifiers
- cost sensitive boosting
- minimum mean squared error
- training set
- denoising
- naive bayes
- generalization error
- binary classification problems
- multiclass classification