tidypredict_test
Compares the results of predict() and tidypredict_to_column() functions.
tidypredict_test(model, df = model$model, threshold = 1e-12,
include_intervals = FALSE, max_rows = NULL)Arguments
| model | An R model or a tibble with a parsed model. It currently supports lm(), glm() and randomForest() models. |
| df | A data frame that contains all of the needed fields to run the prediction. It defaults to the "model" data frame object inside the model object. |
| threshold | The number that a given result difference, between predict() and tidypredict_to_column() should not exceed. For continuous predictions, the default value is 0.000000000001 (1e-12), for categorical predictions, the default value is 0. |
| include_intervals | Switch to indicate if the prediction intervals should be included in the test. It defaults to FALSE. |
| max_rows | The number of rows in the object passed in the df argument. Highly recommended for large data sets. |
Examples
library(dplyr)
df <- mutate(mtcars, cyl = paste0("cyl", cyl))
model <- lm(mpg ~ wt + cyl * disp, offset = am, data = df)
tidypredict_test(model)#> tidypredict test results
#> Difference threshold: 1e-12
#>
#> All results are within the difference threshold