Calculate the confusion matrix — calc_confusion

Calculates the confusion matrix of observed and predicted classes, after converting them into factors first (not currently done by conf_mat{yardstick}).

calc_confusion_matrix(x, target_col_name, target_pred_col_name, ...)

Arguments

x	A data frame with two columns: the column with the actual classes; and the column with the predicted classes. Any other columns will be ignored.
target_col_name	A string with the column name of the target variable.
target_pred_col_name	A string with the column name of the predictions for the target variable.
...	Further arguments passed from other methods.

Value

An object with class conf_mat() (see conf_mat{yardstick}).

Examples

library(experienceAnalysis)
mtcars %>%
  dplyr::mutate(carb_pred = sample(carb, size = nrow(.))) %>%  # Mock predictions column
  calc_accuracy_per_class(
    target_col_name = "carb",
    target_pred_col_name = "carb_pred"
  )
#> # A tibble: 6 x 2
#>    carb accuracy
#>   <dbl>    <dbl>
#> 1     1    0.429
#> 2     2    0.1  
#> 3     3    0    
#> 4     4    0.3  
#> 5     6    0    
#> 6     8    0    

# Custom column names
mtcars %>%
  dplyr::mutate(carb_pred = sample(carb, size = nrow(.))) %>%  # Mock predictions column
  calc_confusion_matrix(
    target_col_name = "carb",
    target_pred_col_name = "carb_pred"
  )
#>           Truth
#> Prediction 1 2 3 4 6 8
#>          1 0 3 1 2 0 1
#>          2 2 2 2 4 0 0
#>          3 0 2 0 1 0 0
#>          4 5 2 0 2 1 0
#>          6 0 1 0 0 0 0
#>          8 0 0 0 1 0 0