This function uses the MICE methodology to impute missing values.
Arguments
- df
Dataframe. Dataframe to transform.
- m
Integer. Number of multiple imputations.
- iters
Integer. Number of iterations.
- seed
Integer. Set a seed for reproducibility.
- quiet
Boolean. Keep quiet? (or print replacements).
See also
Other Data Wrangling:
balance_data(),
categ_reducer(),
cleanText(),
date_cuts(),
date_feats(),
file_name(),
formatHTML(),
holidays(),
left(),
normalize(),
num_abbr(),
ohe_commas(),
ohse(),
quants(),
removenacols(),
replaceall(),
replacefactor(),
textFeats(),
textTokenizer(),
vector2text(),
year_month(),
zerovar()
Other Machine Learning:
ROC(),
conf_mat(),
export_results(),
gain_lift(),
h2o_automl(),
h2o_predict_API(),
h2o_predict_MOJO(),
h2o_predict_binary(),
h2o_predict_model(),
h2o_selectmodel(),
iter_seeds(),
lasso_vars(),
model_metrics(),
model_preprocess(),
msplit()
Other Missing Values:
missingness()