Estimating expected error rates of random forest classifiers: A comparison of cross-validation and bootstrap.
Milica LjumovicMichael KlarPublished in: MECO (2015)
Keyphrases
- cross validation
- random forest
- expected error
- training set
- decision trees
- generalization error
- support vector
- feature set
- fold cross validation
- base classifiers
- random forests
- model selection
- ensemble learning
- nearest neighbor classifiers
- learning machines
- training data
- hyperparameters
- binary classifiers
- nearest neighbor
- feature selection
- classification accuracy
- active learning
- classification error
- ensemble methods
- data sets
- support vector machine
- logistic regression
- training examples
- binary classification
- ls svm
- test set
- multi label
- classification algorithm
- svm classifier
- machine learning algorithms
- naive bayes
- supervised learning
- lower bound
- neural network
- generalization ability
- unlabeled data
- graph cuts
- meta learning
- multi class
- face recognition