MIAC: Mutual-Information Classifier with ADASYN for Imbalanced Classification.
Yanyu CaoXiaodong ZhaoZhiping ZhouYufei ChenXianhui LiuYongming LangPublished in: SPAC (2018)
Keyphrases
- mutual information
- feature selection
- classification scheme
- classification method
- classification process
- support vector
- classification algorithm
- binary classification problems
- feature space
- learning vector quantization
- class labels
- support vector machine
- training set
- classification accuracy
- feature set
- classification rate
- classification models
- decision trees
- svm classifier
- classifier combination
- nearest neighbor classifier
- final classification
- feature extraction
- higher classification accuracy
- class imbalance
- k nearest neighbour
- conditional mutual information
- multi category
- probabilistic classifiers
- information gain
- training data
- information theoretic
- training samples
- ensemble classifier
- image classification
- extracted features
- pattern recognition
- feature vectors
- multiple classifier systems
- multiple classifiers
- image registration
- text classification
- selection criterion
- bayesian classifier
- binary classifiers
- decision boundary
- machine learning
- class distribution
- pattern classification
- imbalanced data sets
- active learning
- single class
- individual classifiers
- imbalanced data
- multiclass classification
- multi class
- nearest neighbour
- multi class problems
- training dataset
- supervised learning
- learning phase