Confidence Intervals for Random Forests in Python
نویسندگان
چکیده
منابع مشابه
Confidence Intervals for Random Forests Confidence Intervals for Random Forests: The Jackknife and the Infinitesimal Jackknife
We study the variability of predictions made by bagged learners and random forests, and show how to estimate standard errors for these methods. Our work builds on variance estimates for bagging proposed by Efron (1992, 2012) that are based on the jackknife and the infinitesimal jackknife (IJ). In practice, bagged predictors are computed using a finite number B of bootstrap replicates, and worki...
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We study the variability of predictions made by bagged learners and random forests, and show how to estimate standard errors for these methods. Our work builds on variance estimates for bagging proposed by Efron (1992, 2013) that are based on the jackknife and the infinitesimal jackknife (IJ). In practice, bagged predictors are computed using a finite number B of bootstrap replicates, and worki...
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ژورنال
عنوان ژورنال: The Journal of Open Source Software
سال: 2017
ISSN: 2475-9066
DOI: 10.21105/joss.00124