Statistics: Difference between revisions
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* Bootstrap mean is approximately a posterior average. | * Bootstrap mean is approximately a posterior average. | ||
* Bootstrap aggregation or bagging average: Average the prediction over a collection of bootstrap samples, thereby reducing its variance. The bagging estimate is defined by | * Bootstrap aggregation or bagging average: Average the prediction over a collection of bootstrap samples, thereby reducing its variance. The bagging estimate is defined by | ||
<math>\hat{f}_{bag}(x) = \frac{1}{B}\sum_{b=1}^B \hat{f}^{*b}(x).</math> | :<math>\hat{f}_{bag}(x) = \frac{1}{B}\sum_{b=1}^B \hat{f}^{*b}(x).</math> | ||
* ksjlfda | |||
Revision as of 11:08, 1 April 2013
Boxcox transformation
Finding transformation for normal distribution
Visualize the random effects
http://www.quantumforest.com/2012/11/more-sense-of-random-effects/
ROC curve and Brier score
Elements of Statistical Learning
Bagging
Chapter 8 of the book.
- Bootstrap mean is approximately a posterior average.
- Bootstrap aggregation or bagging average: Average the prediction over a collection of bootstrap samples, thereby reducing its variance. The bagging estimate is defined by
- [math]\displaystyle{ \hat{f}_{bag}(x) = \frac{1}{B}\sum_{b=1}^B \hat{f}^{*b}(x). }[/math]
- ksjlfda