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The bootstrap is a resampling method to estimate the sampling distribution of a statistic.

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bootstrapping: on average, 78% (7 out of 9) of the variables in original model entered the models generated for the 100 bootstrap samples. On the other hand, only 41% (7 out of 17), for the other … the bootstrap samples, and then argue that those that enter more frequently are more likely to be significant? Could I say that there is evidence that the original feature set is relevant in …
asked Oct 17 '14 by Puzzled
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times in order to reduce randonmess and to average the error curves. UPDATE1: I followed a suggestion below and re-ran lasso using bootstrap samples. I had it a go with 100 samples (that amount was … variables are among the 9 that entered the model when I had run it with the original sample and were the ones with the highest coefficient values then. If I run lasso with say 1000 bootstrap samples …
asked Oct 8 '14 by Puzzled