tidy predict

tidy predict

tidy_predict(
  model,
  newdata,
  form = NULL,
  olddata = NULL,
  bind_preds = FALSE,
  ...
)

# S3 method for Rcpp_ENSEMBLE
tidy_predict(model, newdata, form = NULL, ...)

# S3 method for glm
tidy_predict(model, newdata, form = NULL, ...)

# S3 method for default
tidy_predict(model, newdata, form = NULL, ...)

# S3 method for BinaryTree
tidy_predict(model, newdata, form = NULL, ...)

# S3 method for xgb.Booster
tidy_predict(
  model,
  newdata,
  form = NULL,
  olddata = NULL,
  bind_preds = FALSE,
  ...
)

# S3 method for lgb.Booster
tidy_predict(
  model,
  newdata,
  form = NULL,
  olddata = NULL,
  bind_preds = FALSE,
  ...
)

Arguments

model

model

newdata

dataframe

form

the formula used for the model

olddata

training data set

bind_preds

set to TURE if newdata is a dataset without any labels, to bind the new and old data with the predictions under the original target name

...

other parameters to pass to predict

Value

dataframe

Examples

iris %>%
 framecleaner::create_dummies(Species) -> iris_dummy
#> 1 column(s) have become 3 dummy columns

iris_dummy %>%
 tidy_formula(target= Petal.Length) -> petal_form

iris_dummy %>%
 tidy_xgboost(
   petal_form,
   trees = 20,
   mtry = .5
 )  -> xg1
#> accuracy tested on a validation set
#> # A tibble: 3 × 2
#>   .metric .estimate
#>   <chr>       <dbl>
#> 1 ccc         0.671
#> 2 rmse        1.36 
#> 3 rsq         0.955



xg1 %>%
 tidy_predict(newdata = iris_dummy, form = petal_form) %>%
 head()
#> created the following column: Petal.Length_preds_Table
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width species_setosa
#> 1          5.1         3.5          1.4         0.2              1
#> 2          4.9         3.0          1.4         0.2              1
#> 3          4.7         3.2          1.3         0.2              1
#> 4          4.6         3.1          1.5         0.2              1
#> 5          5.0         3.6          1.4         0.2              1
#> 6          5.4         3.9          1.7         0.4              1
#>   species_versicolor species_virginica Petal.Length_preds_Table
#> 1                  0                 0                 1.110146
#> 2                  0                 0                 1.110146
#> 3                  0                 0                 1.110146
#> 4                  0                 0                 1.110146
#> 5                  0                 0                 1.110146
#> 6                  0                 0                 1.110146