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Fixed typo (#145)

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Brandon Greenwell 2016-07-22 12:24:59 -04:00 committed by Hadley Wickham
parent 05a0efe27c
commit bcd8a84bbe
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model-assess.Rmd
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@ -38,7 +38,7 @@ There are two main resampling techniques that we're going to cover.
the data to the training set, and evaluate it on the test set. This avoids
intrinsic bias of using the same data to both fit the model and assess it's
quality. However it introduces a new bias: you're not using all the data to
fit the model so it's going to be quite as good as it could be.
fit the model so it's not going to be quite as good as it could be.
* We will use __boostrapping__ to understand how stable (or how variable)
the model is. If you sample data from the same population multiple times,