Compares the results of predict() and tidypredict_to_column() functions.
Usage
tidypredict_test(
model,
df = model$model,
threshold = 1e-12,
include_intervals = FALSE,
max_rows = NULL,
xg_df = NULL
)Arguments
- model
An R model or a list 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), and 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.
- xg_df
A xgb.DMatrix object, required only for XGBoost models. It defaults to NULL recommended for large data sets.
Examples
model <- lm(mpg ~ wt + cyl * disp, offset = am, data = mtcars)
tidypredict_test(model)
#> tidypredict test results
#> Difference threshold: 1e-12
#>
#> All results are within the difference threshold