Hi @SophieCuvillier,
The selection of columns may be the explanation in difference of results we have. Another option if you don't want to have imputed values in some columns could be to use the option "Save Scoring Formula to Current Data Table", so that new columns with imputed values are created, enabling you to assess the relevance of the imputed values, selecting the imputed column you want in visualization or modeling, and/or also enabling you to better assess the impact (and benefits ?) of imputation method on the modeling results.
Unlike other imputation methods, the more columns the better for ADI, as it uses the information from the other covariates to impute missing values. To avoid data leakage (info from validation/test sets used in the training and data imputation), a validation column should be used when launching this platform.
A presentation about this platform is available here : Automated Data Imputation: A Versatile Tool in JMP® Pro 14 for Handling Missing ... - JMP User Commu...
And more info about the method can be found here : The Missing Value Report
I hope this complementary answer will help you,
Victor GUILLER
L'Oréal Data & Analytics
"It is not unusual for a well-designed experiment to analyze itself" (Box, Hunter and Hunter)