Adaptively coping with concept drifts in energy time series forecasting using profiles.
Benedikt HeidrichNicole LudwigMarian TurowskiRalf MikutVeit HagenmeyerPublished in: e-Energy (2022)
Keyphrases
- concept drift
- data streams
- streaming data
- evolving data streams
- data stream mining
- ensemble classification
- concept drifting data streams
- non stationary
- incremental clustering
- classification algorithm
- predictive coding
- batch learning
- data distribution
- drift detection
- change detection
- ensemble classifier
- data stream classification
- mining data streams
- stream data
- ensemble learning
- anomaly detection
- stream mining
- sliding window
- high dimensional datasets
- machine learning
- closed frequent itemsets
- semi supervised learning
- decision trees