Analyses numeric variables in a data frame and recommends suitable transformations based on skewness and excess kurtosis. The function does not modify the data; it only provides transformation recommendations to assist with preprocessing before statistical modelling or machine learning.
Value
A list containing:
- recommendations
A data frame of features requiring transformation (excluding
"None").- n_numeric
Number of numeric variables analysed.
- n_recommended
Number of variables for which a transformation was recommended.
- variables
A complete data frame of all analysed numeric features and their metrics.
Details
Recommendations are based on:
Distribution skewness.
Excess kurtosis (tail heaviness).
Whether the variable contains non-positive values.
Possible recommendations include:
None
Log
Box-Cox
Yeo-Johnson
Examples
recommend_transform(iris)
#> $recommendations
#> [1] variable skewness kurtosis finding recommendation
#> <0 rows> (or 0-length row.names)
#>
#> $n_numeric
#> [1] 4
#>
#> $n_recommended
#> [1] 0
#>
#> $variables
#> variable skewness kurtosis finding recommendation
#> 1 Sepal.Length 0.3149110 -0.552064 Approximately symmetric None
#> 2 Sepal.Width 0.3189657 0.228249 Approximately symmetric None
#> 3 Petal.Length -0.2748842 -1.402103 Approximately symmetric None
#> 4 Petal.Width -0.1029667 -1.340604 Approximately symmetric None
#>