Preimplemented Loss Functions

loss_cross_entropy(observed, predicted, p_min = 1e-04, na.rm = TRUE)

observed | observed scores or labels, these are supplied as explainer specific `y` |
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predicted | predicted scores, either vector of matrix, these are returned from the model specific `predict_function()`` |

p_min | for cross entropy, minimal value for probability to make sure that `log` will not explode |

na.rm | logical, should missing values be removed? |

numeric - value of the loss function

library("randomForest") HR_rf_model <- randomForest(status~., data = HR, ntree = 100) loss_cross_entropy(HR$status, yhat(HR_rf_model))#> [1] 5704.802