Self-adaptive modelling algorithms
β Scribed by D.G. Green; R.E. Reichelt; R.G. Buck
- Publisher
- Elsevier Science
- Year
- 1988
- Tongue
- English
- Weight
- 398 KB
- Volume
- 30
- Category
- Article
- ISSN
- 0378-4754
No coin nor oath required. For personal study only.
β¦ Synopsis
Self-adaptive" algorithms include a wide variety of procedures that derive models by "training" with data about the process concerned. Adaptive algorithms typically perform brilliantly under some conditions, but fail badly under others. Flexibility, reliability and speed are prime concerns in designing and using such algorithms.
π SIMILAR VOLUMES
We study on-line learning in the linear regression framework. Most of the performance bounds for on-line algorithms in this framework assume a constant learning rate. To achieve these bounds the learning rate must be optimized based on a posteriori information. This information depends on the whole