Podcast #128: We chat with Kent C Dodds about why he loves React and discuss what life was like in the dark days before Git. Listen now.
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Creating samples from a well-specified population using a probabilistic method and/or producing random numbers from a specified distribution. As this tag is ambiguous, please consider [survey-sampling] for the former and [monte-carlo] or [simulation] for the latter. For questions regarding creating random samples from known distributions, please consider using the [random-generation] tag.

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sampling technique, which is claimed to "to improve the stability and accuracy of machine learning algorithms". The technique withdraws the same sample more than one time and completely ignores other …
asked Nov 13 '13 by Error404
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I am constructing a model for the prediction of a binary (Yes/No) outcome. I have a learning sample that gives the machine 1500 examples of the "Yes" group and 500 example of the "No" group. Should I …
asked Aug 9 '13 by Error404
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would like to make my learning sample equal in number for both variables (i.e. 1000 row that belongs to A and 1000 row that belongs to B). A random sampling technique might be very biased when selecting … 1000 out of 6000 rows. What would be the best way to pick these 1000 samples from group A in a way that assures this is not a biased sampling? In other words, I would like to have a sample of 1000 rows that represent as closely as possible the 6000 rows. What technique would do this best? …
asked Aug 19 '13 by Error404