Learning under concept drift with follow the regularized leader and adaptive decaying proximal
Concept drift is the problem that the statistical properties of the data generating process change over time. Recently, the Time Decaying Adaptive Prediction (TDAP) algorithm1 was proposed to address the problem of concept drift. TDAP was designed to account for the effect of drifting concepts by di...
| Huvudupphovsmän: | , , |
|---|---|
| Övriga upphovsmän: | |
| Materialtyp: | Journal Article |
| Språk: | English |
| Publicerad: |
2018
|
| Ämnen: | |
| Länkar: | https://hdl.handle.net/10356/87712 http://hdl.handle.net/10220/45494 |