Predicting the Influence of Additional Training Data on Classification Performance for Imbalanced Data.
Stephen KockentiedtKlaus D. TönniesErhardt GierkePublished in: GCPR (2014)
Keyphrases
- imbalanced data
- training data
- classification models
- classification accuracy
- decision trees
- class distribution
- training set
- class imbalance
- support vector machine
- imbalanced data sets
- supervised learning
- imbalanced datasets
- minority class
- decision boundary
- feature selection
- class labels
- linear regression
- training samples
- pattern classification
- machine learning
- feature extraction
- data sets
- svm classifier
- support vector
- ensemble classifier
- image classification
- ensemble methods
- support vector machine svm
- random forest
- machine learning methods
- cost sensitive
- dimensionality reduction
- classification error
- least squares
- knn
- active learning
- test data
- sampling methods
- decision rules
- benchmark datasets
- learning algorithm
- text classification