impute_missing_features: Impute missing features with the median, plus or minus some...
In fosterlab/CFTK: The Co-Fractionation Toolkit

Replace missing data within each numeric column of a data frame with the column median, plus or minus some random noise, in order to train classifiers that do not readily ignore missing data (e.g. random forests or support vector machines).

1	impute_missing_features(dat, noise_pct = 0.05)

`dat`	the feature data frame for which to replace missing data
`noise_pct`	the standard deviation of the random normal distribution from which to draw added noise, expressed as a percentage of the standard deviation of the non-missing values in each column

a data frame with missing values in each numeric column replaced by the column median, plus or minus some random noise

fosterlab/CFTK documentation built on Jan. 19, 2021, 10:31 p.m.