Cost-sensitive steganalysis with stochastic sensitvity and cost sensitive training error.
Zhi-Min HePublished in: ICMLC (2012)
Keyphrases
- cost sensitive
- boosting algorithms
- training error
- multi class
- misclassification costs
- binary classification
- multiclass classification
- base classifiers
- base learners
- class distribution
- active learning
- naive bayes
- class imbalance
- support vector machine
- generalization error
- adaboost algorithm
- classification error
- error rate
- binary classifiers
- hidden layer
- neural network
- classification accuracy
- feature extraction
- gradient method
- feature selection