lares (version 5.0.3)

impute: Impute Missing Values (using MICE)

Description

This function uses the MICE methodology to impute missing values.

Usage

impute(df, m = 5, iters = 5, seed = 0, quiet = FALSE)

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).

Value

data.frame with imputed values.

See Also

Other Data Wrangling: balance_data(), categ_reducer(), cleanText(), date_cuts(), date_feats(), formatNum(), holidays(), left(), normalize(), numericalonly(), ohe_commas(), ohse(), removenacols(), removenarows(), replaceall(), textFeats(), textTokenizer(), vector2text(), year_month(), year_week()

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()