> Hello. I have data that is 45 trials, each 60 samples long. I have heard > bootstrapping can resample it to give "new" data that can be used in > classifier training. Can I just double-check that this is the correct way > to do it: > > bootx=bootstrp(500, 'mean', x); > > where x is my original data and I want 500 new rows generated through > bootstrapping. Thanks.
This doesn't really increase the sample size. If you randomly resample from your data and append it to the data as if it were new, that would artificially increase the sample size and make your results look more accurate then they are.
Your function randomly applies the "mean" function to 500 new samples taken from x. It gives you an idea of how uncertain your estimate of the mean of x is. The result bootx will not look like x, but instead have a smaller standard deviation centered around the mean of x.
Sadly I don't have any experience with using bootstrapping in connection with classifier training, so I can't offer anything special there.