FSharp.Stats already supports the KNN imputation via FSharp.Stats.ML.Impute.kNearestImpute. The current implementation takes the k nearest neighbors and computes the average of these at the index of interest. This average replaces the missing value of the incomplete data point. I suggest to make the following changes/additions:
rename the module to Imputation to be consistent within the library
add the possibility to define how a missing value is encoded (e.g., 0.0 or nan)
add an optional converter function that processes the distance measure. When using Pearson's correlation coefficient you determine the similarity rather the distance and therefore you have to take the reciprocal.
add a weighted version in which the averaging can be weighted according to the distance of the nearest neighbors
FSharp.Stats already supports the KNN imputation via
FSharp.Stats.ML.Impute.kNearestImpute. The current implementation takes the k nearest neighbors and computes the average of these at the index of interest. This average replaces the missing value of the incomplete data point. I suggest to make the following changes/additions:Imputationto be consistent within the libraryKeywords