hcai_impute | R Documentation |
'hcai-impute' adds various imputation methods to an existing recipe. Currently supports mean (numeric only), new_category (categorical only), bagged trees, or knn.
hcai_impute( recipe, nominal_method = "new_category", numeric_method = "mean", numeric_params = NULL, nominal_params = NULL )
recipe |
A recipe object. imputation will be added to the sequence of operations for this recipe. |
nominal_method |
Defaults to |
numeric_method |
Defaults to |
numeric_params |
A named list with parmeters to use with
chosen imputation method on numeric data. Options are
|
nominal_params |
A named list with parmeters to use with
chosen imputation method on nominal data. Options are
|
An updated version of 'recipe' with the new step added to the sequence of existing steps.
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
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