replace_missing_data: Replace missing data with median ± random noise
In PrInCE: Predicting Interactomes from Co-Elution

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 easily ignore missing data (e.g. random forests or support vector machines).

1	replace_missing_data(dat, noise_pct = 0.05)

`dat`	the data frame to replace missing data in
`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

PrInCE documentation built on Nov. 8, 2020, 6:34 p.m.