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SADEM: An Effective Supervised Anomaly Detection Ensemble Model for Alert Account Detection
Hui Kuo Yang
*
, Bing Li Su,
Wen Chih Peng
*
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Keyphrases
Ensemble Model
100%
Anomaly Detection Ensembles
100%
Semi-supervised Anomaly Detection
100%
SADEM
100%
Confident Prediction
100%
Anomaly Detection
66%
Supervised Learning Method
66%
High Cost
33%
Multilayer Perceptron
33%
Transaction Data
33%
Real-world Application
33%
Semi-supervised Learning
33%
State-of-the-art Techniques
33%
Supervised Learning
33%
Neural Network Model
33%
Detection Task
33%
Synergize
33%
Leaf Nodes
33%
Ensemble Methods
33%
Gradient Boosting Decision Tree
33%
Machine Learning Network
33%
Learning Network Models
33%
LightGBM
33%
Learning Ensembles
33%
Computer Science
Anomaly Detection
100%
Supervised Learning
66%
Multilayer Perceptron
33%
Semisupervised Learning
33%
Research Topic
33%
Neural Network Model
33%
World Application
33%
Learning Approach
33%
Transaction Data
33%
Learning Network
33%
Ensemble Method
33%
Gradient Boosting
33%
Normal Data Point
33%
Machine Learning
33%
Learning System
33%
Decision Tree
33%