Difference between revisions of "Online machine learning"
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* Arrive in a high speed stream and then must be discarded to make room for subsequent examples. | * Arrive in a high speed stream and then must be discarded to make room for subsequent examples. | ||
* Algorithm must update its model incrementally as each element is inspected. | * Algorithm must update its model incrementally as each element is inspected. | ||
| + | * It should ideally be able to apply the model any time between training examples. | ||
Revision as of 13:31, 24 March 2012
Stream mining
- Core assumption is that training examples can be briefly inspected for a single time only.
- Arrive in a high speed stream and then must be discarded to make room for subsequent examples.
- Algorithm must update its model incrementally as each element is inspected.
- It should ideally be able to apply the model any time between training examples.
