An Empirical Boosting Scheme for ROC-Based Genetic Programming Classifiers.
Denis RobilliardVirginie Marion-PotySébastien MahlerCyril FonluptPublished in: EuroGP (2007)
Keyphrases
- genetic programming
- feature selection
- ensemble learning
- roc curve
- receiver operating characteristic
- weak learners
- training data
- fitness function
- randomized trees
- evolutionary computation
- ensemble classifier
- evolutionary algorithm
- weak classifiers
- decision stumps
- symbolic regression
- boosting algorithms
- adaboost algorithm
- genetic algorithm
- roc analysis
- majority voting
- discriminative classifiers
- machine learning methods
- improving classification accuracy
- classification algorithm
- accurate classifiers
- test set
- boosting framework
- decision trees
- weighted voting
- gene expression programming
- financial forecasting
- machine learning
- multiclass classification
- grammar guided genetic programming
- linear classifiers
- combining multiple
- machine learning algorithms
- combining classifiers
- learning algorithm
- support vector
- boosted classifiers
- classification accuracy
- naive bayes
- training examples
- class labels
- classification trees
- svm classifier
- cross validation
- ensemble methods
- random forests
- learning scheme
- regression problems