Comments (1)
callowbird
commented on July 30, 2024
Thanks. In table 3, the feature 1-5 is X4, which has negative weight, showing that we want X4=1, i.e., learning rate <0.01.
Then, the feature 1-3 is X4X5, with positive weight, showing that we want X4X5=-1, so X5=-1. That is, [0.001,0.01].
Such inference is not necessary in the algorithm, as we simply enumerate all possibilities of all selected hyperparameters.
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Related Issues (3)
- Experiments with Synthetic functions HOT 7
- Add license file HOT 1
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