Sparse grid classifiers as base learners for AdaBoost.
Alexander HeineckeBenjamin PeherstorferDirk PflügerZhongwen SongPublished in: HPCS (2012)
Keyphrases
- object detection
- base learners
- ensemble methods
- ensemble learning
- meta learning
- base classifiers
- multi class
- classification algorithm
- decision trees
- learning scheme
- decision stumps
- random forests
- training data
- cost sensitive
- weak classifiers
- generalization ability
- cross validation
- binary classification problems
- regression problems
- loss function
- learning tasks
- ensemble classifier
- machine learning methods
- prediction accuracy
- learning algorithm
- training process
- machine learning algorithms
- random forest
- high dimensional
- classification models
- naive bayes
- benchmark datasets
- feature selection
- multi task
- support vector
- training set
- inductive learning
- high dimensional data
- learning problems
- feature set
- sparse representation
- class labels
- logistic regression
- support vector machine
- model selection
- training examples
- data sets