The Theory Behind Overfitting, Cross Validation, Regularization, Bagging, and Boosting: Tutorial.
Benyamin GhojoghMark CrowleyPublished in: CoRR (2019)
Keyphrases
- cross validation
- regularization parameter
- base learners
- generalization error
- model selection
- training set
- ensemble methods
- gradient boosting
- ensemble learning
- support vector
- hyperparameters
- regression problems
- variable selection
- boosting algorithms
- base classifiers
- cross validated
- machine learning
- decision trees
- ensemble classification
- error estimates
- feature selection
- meta learning
- prediction accuracy
- binary classification
- information criterion
- learning machines
- unseen data
- decision tree induction
- ls svm
- learning algorithm
- machine learning methods
- nearest neighbor classifiers
- data mining
- kernel machines
- ensemble classifier
- weak classifiers
- class distribution
- generalization ability
- sample size
- loss function
- benchmark datasets