Classification of breast cancer using ensemble filter feature selection with triplet attention based efficient net classifier.
Bangalore Nagaraj MadhukarShivanandamurthy Hiremath BharathiMatta Polnaya AshwinPublished in: Int. Arab J. Inf. Technol. (2024)
Keyphrases
- feature selection
- breast cancer
- clustered microcalcifications
- ensemble classifier
- breast cancer diagnosis
- roc analysis
- classification models
- feature set
- logistic regression
- support vector
- feature ranking
- feature space
- bladder cancer
- classification accuracy
- support vector machine
- computer aided detection
- mammogram images
- fold cross validation
- diagnosis of breast cancer
- feature selection algorithms
- early detection
- computer aided diagnosis
- training set
- text classification
- feature subset
- majority voting
- wrapper method
- svm classifier
- cancer datasets
- classifier ensemble
- feature extraction
- text categorization
- class distribution
- ensemble learning
- training data
- high dimensionality
- microcalcification clusters
- bayesian classifier
- random forest
- decision trees
- machine learning
- ensemble methods
- microarray data
- model selection
- benign and malignant
- base classifiers
- knn
- class imbalance
- multi class
- breast cancer patients
- pixel classification
- class labels
- computer aided
- weak classifiers
- support vector machine svm
- naive bayes
- loss function
- supervised learning
- microarray datasets
- feature vectors