impute: Impute Missing Values (using MICE)

In lares: Analytics & Machine Learning Sidekick

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(), 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_MOJO(), h2o_selectmodel(), iter_seeds(), lasso_vars(), model_metrics(), model_preprocess(), msplit()

Other Missing Values: missingness()

lares documentation built on Sept. 13, 2024, 1:08 a.m.