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Adaboost Learning Rate in Matlab Documentation

조회 수: 4 (최근 30일)
Dario Walter
Dario Walter 2020년 8월 13일
댓글: Dario Walter 2020년 8월 23일
Hey,
the description of Adaboost allows to set a learn rate.
However, the learn rate typically refers to Gradient Boosting. Could anyone explain to me what Matlab is doing when AdaboostM1 is applied.
Thanks for your help!

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Raunak Gupta
Raunak Gupta 2020년 8월 15일
Hi,
The LearnRate option in AdaBoostM1 tells about the learning rate of shrinkage which is essentially the shrink in contribution of each new base-model learned in the ensemble. This parameter controls how much the new model contributes to existing one. Normally if the LearnRate is too small it will require more iterations to get trained and will be more accurate. AdaBoostM1 is used for binary classification problem only.
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Raunak Gupta
Raunak Gupta 2020년 8월 21일
편집: Raunak Gupta 2020년 8월 21일
Hi Dario,
The LearnRate parameter is included while calculate the weights of the weak hypothesis in the ensemble that is () in the Algorithm mentioned here. It is not explained in the original AdaBoost algorithm but is used widely in almost all of the application of AdaBoost because it provides a way to tinker the actual contribution of subsequent weak learners. So when any is calculated for a learner it is multiplied with LearnRate to diminish or enhance its contribution (based on value being < 1 or > 1).
You can see in this example, the influence of different LearnRate.
Dario Walter
Dario Walter 2020년 8월 23일
Thank you Raunak. This helps me a lot.

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