Calculate Loss Functions
Calculate Loss Functions
loss_cross_entropy(observed, predicted, p_min = 1e-04, na.rm = TRUE) loss_sum_of_squares(observed, predicted, na.rm = TRUE) loss_root_mean_square(observed, predicted, na.rm = TRUE) loss_accuracy(observed, predicted, na.rm = TRUE) loss_one_minus_auc(observed, predicted) loss_default(x)
observed |
observed scores or labels, these are supplied as explainer specific |
predicted |
predicted scores, either vector of matrix, these are returned from the model specific |
p_min |
for cross entropy, minimal value for probability to make sure that |
na.rm |
logical, should missing values be removed? |
x |
either an explainer or type of the model. One of "regression", "classification", "multiclass". |
numeric - value of the loss function
library("ranger")
titanic_ranger_model <- ranger(survived~., data = titanic_imputed, num.trees = 50,
probability = TRUE)
loss_one_minus_auc(titanic_imputed$survived, yhat(titanic_ranger_model, titanic_imputed))
HR_ranger_model_multi <- ranger(status~., data = HR, num.trees = 50, probability = TRUE)
loss_cross_entropy(as.numeric(HR$status), yhat(HR_ranger_model_multi, HR))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.