Interpretable CNV-based tumour classification using fuzzy rule based classifiers.
Mattia RicattoMarco BarsacchiAlessio BechiniPublished in: SAC (2018)
Keyphrases
- classification systems
- support vector
- svm classifier
- decision trees
- accurate classification
- classification method
- classification models
- classification algorithm
- classification accuracy
- classification rate
- feature selection
- classification process
- class labels
- training set
- decision boundary
- training samples
- machine learning algorithms
- improves the classification accuracy
- multiple classifiers
- cancer diagnosis
- multi category
- support vector machine
- higher classification accuracy
- support vector machine svm
- machine learning methods
- classification rules
- probabilistic classifiers
- supervised classification
- feature set
- classification procedure
- majority voting
- machine learning
- classifier combination
- ensemble classifier
- classifier ensemble
- nearest neighbor classifier
- image classification
- classification decisions
- multiple classifier systems
- medical images
- binary classifiers
- multiclass classification
- k nearest neighbour
- training data
- learning algorithm
- imbalanced data sets
- combining classifiers
- naive bayes
- feature space
- associative classifiers
- decision tree classifiers
- accurate classifiers
- discriminative classifiers
- feature extraction
- individual classifiers
- fold cross validation