Abstract
An incremental learning algorithm, Learn++, which allows supervised classification algorithms to learn from new data without forgetting previously acquired knowledge, is introduced. Learn++ is based on generating multiple classifiers using strategically chosen distributions of the training data and combining these classifiers through weighted majority voting. Learn++ shares various notions with psycho-physiological models of learning. The Learn++ algorithm, simulation results, and how the algorithm is related to various concepts in psycho-physiological learning models are discussed.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 672-675 |
| Number of pages | 4 |
| Journal | Annual Reports of the Research Reactor Institute, Kyoto University |
| Volume | 1 |
| State | Published - 2001 |
| Externally published | Yes |
| Event | 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Istanbul, Turkey Duration: Oct 25 2001 → Oct 28 2001 |
All Science Journal Classification (ASJC) codes
- Energy Engineering and Power Technology
- Mechanical Engineering