Store predicted values generated in model functions

# S3 method for model.predict
store(dataset, object, name = "prediction", ...)

Arguments

dataset	Dataset to add predictions to
object	Return value from model function
name	Variable name(s) assigned to predicted values
...	Additional arguments

Details

See https://radiant-rstats.github.io/docs/model/regress.html for an example in Radiant

Examples

regress(diamonds, rvar = "price", evar = c("carat", "cut")) %>%
  predict(pred_data = diamonds) %>%
  store(diamonds, ., name = c("pred", "pred_low", "pred_high")) %>%
  head()
#> # A tibble: 6 x 14
#>   price carat clarity cut   color depth table     x     y     z date      
#>   <int> <dbl> <fct>   <fct> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <date>    
#> 1   580  0.32 VS1     Ideal H      61    56    4.43  4.45  2.71 2012-02-26
#> 2   650  0.34 SI1     Very… G      63.4  57    4.45  4.42  2.81 2012-02-26
#> 3   630  0.3  VS2     Very… G      63.1  58    4.27  4.23  2.68 2012-02-26
#> 4   706  0.35 VVS2    Ideal H      59.2  56    4.6   4.65  2.74 2012-02-26
#> 5  1080  0.4  VS2     Prem… F      62.6  58    4.72  4.68  2.94 2012-02-26
#> 6  3082  0.6  VVS1    Ideal E      62.5  53.7  5.35  5.43  3.38 2012-02-26
#> # … with 3 more variables: pred <dbl>, pred_low <dbl>, pred_high <dbl>