Digital mammogram classification using 2D-BDWT and GLCM features with FOA-based feature selection approach.
Figlu MohantySuvendu RupBodhisattva DashBanshidhar MajhiM. N. S. SwamyPublished in: Neural Comput. Appl. (2020)
Keyphrases
- feature selection
- feature set
- classification accuracy
- feature space
- feature extraction
- irrelevant features
- feature selection algorithms
- classification models
- feature subset
- discriminative features
- feature vectors
- high dimensionality
- feature reduction
- informative features
- redundant features
- grey level co occurrence matrix
- selected features
- text classification
- support vector machine
- classification performances
- textural features
- input features
- selecting relevant features
- classification method
- feature weights
- wrapper feature selection
- svm classifier
- extracted features
- feature selection and classification
- feature weighting
- feature ranking
- support vector
- selecting features
- single feature
- machine learning
- select relevant features
- class separability
- unsupervised feature selection
- feature construction
- bayes classifier
- feature subset selection
- feature level fusion
- feature relevance
- class labels
- text categorization
- feature generation
- image classification
- discriminatory power
- decision trees
- individual features
- information gain
- image features
- grey level
- co occurrence
- dimensionality reduction
- texture features
- feature values
- naive bayes
- classification algorithm
- ensemble classifier
- classification process
- training set
- gray level
- supervised learning
- support vector machine svm