AdaCC: cumulative cost-sensitive boosting for imbalanced classification.

Vasileios Iosifidis Symeon Papadopoulos Bodo Rosenhahn Eirini Ntoutsi

Published in: Knowl. Inf. Syst. (2023)

Keyphrases

class imbalance
cost sensitive boosting
cost sensitive
support vector machine
decision trees
classification accuracy
image classification
imbalanced data

class labels
machine learning algorithms
imbalanced data sets
training set
classification algorithm
model selection
binary classification problems

high dimensionality
text classification
feature space
machine learning
benchmark datasets
data sets
active learning

feature vectors
binary classification
support vector
minority class
feature extraction
multi class problems
feature selection