hcai_impute: Specify imputation methods for an existing recipe

In healthcareai: Tools for Healthcare Machine Learning

Specify imputation methods for an existing recipe

Description

'hcai-impute' adds various imputation methods to an existing recipe. Currently supports mean (numeric only), new_category (categorical only), bagged trees, or knn.

Usage

hcai_impute(
  recipe,
  nominal_method = "new_category",
  numeric_method = "mean",
  numeric_params = NULL,
  nominal_params = NULL
)

Arguments

recipe	A recipe object. imputation will be added to the sequence of operations for this recipe.
nominal_method	Defaults to "new_category". Other choices are "bagimpute", "knnimpute" or "locfimpute".
numeric_method	Defaults to "mean". Other choices are "bagimpute", "knnimpute" or "locfimpute".
numeric_params	A named list with parmeters to use with chosen imputation method on numeric data. Options are bag_model (bagimpute only), bag_trees (bagimpute only), bag_options (bagimpute only), bag_trees (bagimpute only), knn_K (knnimpute only), impute_with (knnimpute only), (bag or knn) or seed_val (bag or knn). See step_impute_bag or step_impute_knn for details.
nominal_params	A named list with parmeters to use with chosen imputation method on nominal data. Options are bag_model (bagimpute only), bag_trees (bagimpute only), bag_options (bagimpute only), bag_trees (bagimpute only), knn_K (knnimpute only), impute_with (knnimpute only), (bag or knn) or seed_val (bag or knn). See step_impute_bag or step_impute_knn for details.

Value

An updated version of 'recipe' with the new step added to the sequence of existing steps.

Examples

library(recipes)

n = 100
set.seed(9)
d <- tibble::tibble(patient_id = 1:n,
            age = sample(c(30:80, NA), size = n, replace = TRUE),
            hemoglobin_count = rnorm(n, mean = 15, sd = 1),
            hemoglobin_category = sample(c("Low", "Normal", "High", NA),
                                         size = n, replace = TRUE),
            disease = ifelse(hemoglobin_count < 15, "Yes", "No")
)

# Initialize
my_recipe <- recipe(disease ~ ., data = d)

# Create recipe
my_recipe <- my_recipe %>%
  hcai_impute()
my_recipe

# Train recipe
trained_recipe <- prep(my_recipe, training = d)

# Apply recipe
data_modified <- bake(trained_recipe, new_data = d)
missingness(data_modified)


# Specify methods:
my_recipe <- my_recipe %>%
  hcai_impute(numeric_method = "bagimpute",
    nominal_method = "locfimpute")
my_recipe

# Specify methods and params:
my_recipe <- my_recipe %>%
  hcai_impute(numeric_method = "knnimpute",
    numeric_params = list(knn_K = 4))
my_recipe

healthcareai documentation built on Sept. 5, 2022, 5:12 p.m.