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如何在r中使用整洁的模型对数据进行反规范化_R_Machine Learning Model_Tidymodels_R Recipes - Fatal编程技术网

如何在r中使用整洁的模型对数据进行反规范化

如何在r中使用整洁的模型对数据进行反规范化,r,machine-learning-model,tidymodels,r-recipes,R,Machine Learning Model,Tidymodels,R Recipes,随着tidymodels成为R中开发模型的新工作流,我如何使用tidymodels对电力变换进行反规范化/反转 ddA撰写本文时,没有“步骤撤消”或“工作流”选项,因此您应该手动执行: x=1:5 x #[1] 1 2 3 4 5 normalized = (x-min(x))/(max(x)-min(x)) normalized #[1] 0.00 0.25 0.50 0.75 1.00 denormalized = (normalized)*(max(x)-min(x))+min(x)

随着tidymodels成为R中开发模型的新工作流,我如何使用tidymodels对电力变换进行反规范化/反转


ddA撰写本文时,没有“步骤撤消”或“工作流”选项,因此您应该手动执行:

x=1:5
x
#[1] 1 2 3 4 5

normalized = (x-min(x))/(max(x)-min(x))
normalized
#[1] 0.00 0.25 0.50 0.75 1.00

denormalized = (normalized)*(max(x)-min(x))+min(x)
denormalized
#[1] 1 2 3 4 5
建模时,您可以执行以下操作:

x=1:5
x
#[1] 1 2 3 4 5

normalized = (x-min(x))/(max(x)-min(x))
normalized
#[1] 0.00 0.25 0.50 0.75 1.00

denormalized = (normalized)*(max(x)-min(x))+min(x)
denormalized
#[1] 1 2 3 4 5