| Issue | #Downvotes for this reason | By |
|---|
| error_on_new | If True (default), transform will raise an error when there are features with missing values in transform that have no missing values in fit This is applicable only when ``features="missing-only"``. | default: false |
| features | Whether the imputer mask should represent all or a subset of features - If "missing-only" (default), the imputer mask will only represent features containing missing values during fit time - If "all", the imputer mask will represent all features | default: "missing-only" |
| missing_values | The placeholder for the missing values. All occurrences of `missing_values` will be imputed | default: NaN |
| sparse | Whether the imputer mask format should be sparse or dense - If "auto" (default), the imputer mask will be of same type as input - If True, the imputer mask will be a sparse matrix - If False, the imputer mask will be a numpy array | default: "auto" |