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ERM Baseline #4

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hbsz123 opened this issue Oct 12, 2019 · 1 comment
Open

ERM Baseline #4

hbsz123 opened this issue Oct 12, 2019 · 1 comment

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@hbsz123
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hbsz123 commented Oct 12, 2019

Thanks for sharing your code.

I have ran the ERM baseline but get 73.17% acc, which is different from 70.36% reported in the paper. Is there some problem about my experiment?

image

@AlanChou
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Hi,

I think there's nothing wrong with the ERM baseline. You're getting this "one" better results due to the seed choice for numpy which efftects how the imbalanced data is formed. You can uncomment line 38 in imbalance_cifar.py and make sure you run multiple runs with different "rand_number". You should be able to get similar mean accuracy to the reported one. And even if it's slightly better than the reported results, I don't consider it an issue since the proposed method have achieved better results too when I ran it. Particularly, for imb_type=step, imb_ratio=0.01, the proposed LDAM-DRW achieved 22.3% mean error rate over 10 runs.

I hope the above information helps.

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