Class distribution-aware adaptive margins and cluster embedding for classification of fruit and vegetables at supermarket self-checkouts.
Khurram HameedDouglas ChaiAlexander RassauPublished in: Neurocomputing (2021)
Keyphrases
- class distribution
- class imbalance
- training set
- roc analysis
- imbalanced data sets
- highly skewed
- imbalanced datasets
- cost sensitive
- training samples
- classification algorithm
- highly imbalanced
- pattern classification
- class labels
- image classification
- decision trees
- majority class
- training data
- imbalanced data
- cost sensitive learning
- text classification
- machine learning
- feature selection
- test set
- misclassification costs
- training examples
- feature extraction
- minority class
- decision boundary
- concept drift
- support vector machine
- machine learning methods
- support vector
- learning process
- base classifiers
- supervised learning
- high dimensionality
- data sets
- benchmark datasets
- prediction accuracy