缺失值填充

https://www.analyticsvidhya.com/blog/2016/03/tutorial-powerful-packages-imputing-missing-values/

5种超级棒的缺失值填充R算法包,需要好好实践一下。

List of R Packages

  1. MICE
  2. Amelia
  3. missForest
  4. Hmisc
  5. mi

So, which is the best of these 5 packages ? I am sure many of you would be asking this! Having created this tutorial, I felt Hmisc should be your first choice of missing value imputation followed by missForest and MICE.

Hmisc automatically recognizes the variables types and uses bootstrap sample and predictive mean matching to impute missing values. You don’t need to separate or treat categorical variable, just like we did while using MICE package. However, missForest can outperform Hmisc if the observed variables supplied contain sufficient information.

原文地址:https://www.cnblogs.com/xinping-study/p/7007533.html