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In your case, you have first to deal with the biological data complexity. I don't know the minimum sampling rate to detect brain epilepsia or any brain behavior. I would recommend to study some articles to know the best practices about EEG signal analysis like this one : https://www.frontiersin.org/articles/10.3389/fneur.2020.00375/full Maybe there are good ...


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This would need some data preprocessing: Get the different main categories (ex: bikes and car) If there are several mix of categories, get the quantities of each configuration in order to get the right proportions of the samples (see 4). Get random sample within each category (10% bikes and 10% cars) Ensure that those samples have the right quantity in ...


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I agree with ‘Carlos Mougan,’ and add the comparison with these models. Basically, GB(Breiman 1996, 1999)、SGB(Friedman 2002) and XGB(Chen and Guestrin 2016) do sampling w/o replacement. GB uses the full sample set for each iteration. Thus, GB performs like sampling w/o replacement. So, the three use sampling w/o replacement by tradition. However, bagging and ...


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