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GMOTE: Gaussian based minority oversampling technique for imbalanced classification adapting tail probability of outliers.
Seung Jee Yang
Kyung Joon Cha
Published in:
CoRR (2021)
Keyphrases
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class imbalance
minority class
class distribution
majority class
class imbalanced
cost sensitive learning
decision boundary
classification accuracy
cost sensitive
support vector machine svm
pattern classification
imbalanced datasets
high dimensionality
support vector machine
support vector
pattern recognition
feature selection
classification method
single class
class conditional
training set
imbalanced data sets
class membership
feature extraction
imbalanced data
training samples
classification error
classification models
probability distribution
machine learning methods
text classification
nearest neighbour
feature vectors
active learning
training data
machine learning
svm classifier
highly imbalanced