A general framework for mining concept-drifting data streams with skewed distributions

Keyphrases

• Skewed Distribution 100%
• Concept Drift 100%
• Undersampling 50%
• Predictive Modeling 50%
• Prediction Accuracy 50%
• Posterior Probability 50%
• Repeated Sampling 50%
• Stream Application 50%
• Ensemble Model 50%
• Negative Samples 50%
• Estimation Reliability 50%
• Stochastic Distribution 50%

Mathematics

• Estimated Probability 100%
• Skewed Distribution 100%
• Probability Theory 50%
• Stochastics 50%
• Predictive Modeling 50%

Computer Science

• Data Stream 100%
• Estimated Probability 40%
• Posterior Probability 20%