dm.cs.tu-dortmund.de/mlbits/class-ensembles-boosting/
Boosting and Adaboost – Lecture Notes
\(\varepsilon \approx 0.25\)
\(\beta \approx 0.333\)
\(\varepsilon \approx 0.167\)
\(\beta \approx 0.2\)
Boosting – Example
Toy example for boosting, using 1-node decision stumps:
\(0.981\cdot\)
\(+1.099\cdot\) [...] gradient boosting. Comput. Stat. Data Anal. 38, 4 (2002), 367–378. DOI: 10.1016/S0167-9473(01)00065-2
[FrSc97]
Freund, Y. and Schapire, R.E. 1997. A decision-theoretic generalization of on-line learning …
