Using Machine Learning for Automated Assessment of Misclassification of Goods for Fraud Detection.
Margarita SpichakovaHele-Mai HaavPublished in: DB&IS (2020)
Keyphrases
- fraud detection
- cost sensitive
- machine learning
- cost sensitive learning
- data mining
- credit card fraud detection
- outlier detection
- network intrusion detection
- active learning
- misclassification costs
- rare events
- data mining techniques
- credit card fraud
- credit card
- social network analysis
- multi class
- knowledge discovery
- support vector machine
- semi supervised learning
- information extraction
- supervised learning
- class distribution
- decision trees
- text mining
- network anomaly detection
- text classification
- counter terrorism
- learning algorithm
- data sets
- class imbalance
- video sequences
- error rate
- electronic commerce
- naive bayes
- natural language processing