impute_data {imanr}

Impute the data implementing random forest for native corn data.

Description

Impute and prepare a dataframe to apply the find_racialcomplex() function, in case the dataframe has missing values. The imputation is done with random forests. The database must have the same variables as those in bdMaiz.rds in this same package.

Usage

impute_data(data, useParallel = FALSE)

Arguments

data

An incomplete dataset that contains qualitative and quantitative characteristics of a corn or series of corns. The selected characteristics are related to colors, some measurements, and the locations in which the corn was grown. A template for what has to be filled will be included on the GitHub page of the project.

useParallel

Logical. Perform the analysis in parallel? Defaults to FALSE.

Value

impute_data()returns an imputed dataset that can be used with find_racialcomplex().

Author(s)

Rafael Nieves-Alvarez ([e-mail]), Arturo Sanchez-Porras, Aline Romero-Natale, Otilio Arturo Acevedo-Sandoval

References

Báez Vergara, K. J. Estimación de datos faltantes a través de redes neuronales, una comparación con métodos simples y múltiples (Doctoral dissertation, Universidad Santo Tomás).

See Also

[find_racialcomplex()]

Examples

set.seed(42)
df <- data24[17,]
df

df_imp <- impute_data(df, useParallel = FALSE)
df_imp