Hello guy,
Does the second stage train with the exact same training samples as the first stage or just with 0.5x of the negative samples (maxFalseAlarmRate = 0.5). The 0.5 neg sampels which were classified false?
If yes:
Why does the second stage needs more features to separate the data?
If no:
Is the amount of negative samples decreasing each stage by 0.5? After 20 stages there would be nearly no samples?
I hope the question is understandable,
Thanks a lot for your help!!!
Kind regards,
Derrick
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