View source: R/choosing_metrics_functions.R
multinomial_metrics | R Documentation |
Enable/disable metrics for multinomial evaluation. Can be supplied to the
`metrics`
argument in many of the cvms
functions.
Note: Some functions may have slightly different defaults than the ones supplied here.
multinomial_metrics(
all = NULL,
overall_accuracy = NULL,
balanced_accuracy = NULL,
w_balanced_accuracy = NULL,
accuracy = NULL,
w_accuracy = NULL,
f1 = NULL,
w_f1 = NULL,
sensitivity = NULL,
w_sensitivity = NULL,
specificity = NULL,
w_specificity = NULL,
pos_pred_value = NULL,
w_pos_pred_value = NULL,
neg_pred_value = NULL,
w_neg_pred_value = NULL,
auc = NULL,
kappa = NULL,
w_kappa = NULL,
mcc = NULL,
detection_rate = NULL,
w_detection_rate = NULL,
detection_prevalence = NULL,
w_detection_prevalence = NULL,
prevalence = NULL,
w_prevalence = NULL,
false_neg_rate = NULL,
w_false_neg_rate = NULL,
false_pos_rate = NULL,
w_false_pos_rate = NULL,
false_discovery_rate = NULL,
w_false_discovery_rate = NULL,
false_omission_rate = NULL,
w_false_omission_rate = NULL,
threat_score = NULL,
w_threat_score = NULL,
aic = NULL,
aicc = NULL,
bic = NULL
)
all |
Enable/disable all arguments at once. (Logical) Specifying other metrics will overwrite this, why you can
use ( |
overall_accuracy |
|
balanced_accuracy |
|
w_balanced_accuracy |
|
accuracy |
|
w_accuracy |
|
f1 |
|
w_f1 |
|
sensitivity |
|
w_sensitivity |
|
specificity |
|
w_specificity |
|
pos_pred_value |
|
w_pos_pred_value |
|
neg_pred_value |
|
w_neg_pred_value |
|
auc |
|
kappa |
|
w_kappa |
|
mcc |
Multiclass Matthews Correlation Coefficient. |
detection_rate |
|
w_detection_rate |
|
detection_prevalence |
|
w_detection_prevalence |
|
prevalence |
|
w_prevalence |
|
false_neg_rate |
|
w_false_neg_rate |
|
false_pos_rate |
|
w_false_pos_rate |
|
false_discovery_rate |
|
w_false_discovery_rate |
|
false_omission_rate |
|
w_false_omission_rate |
|
threat_score |
|
w_threat_score |
|
aic |
AIC. (Default: FALSE) |
aicc |
AICc. (Default: FALSE) |
bic |
BIC. (Default: FALSE) |
Ludvig Renbo Olsen, r-pkgs@ludvigolsen.dk
Other evaluation functions:
binomial_metrics()
,
confusion_matrix()
,
evaluate()
,
evaluate_residuals()
,
gaussian_metrics()
# Attach packages
library(cvms)
# Enable only Balanced Accuracy
multinomial_metrics(all = FALSE, balanced_accuracy = TRUE)
# Enable all but Balanced Accuracy
multinomial_metrics(all = TRUE, balanced_accuracy = FALSE)
# Disable Balanced Accuracy
multinomial_metrics(balanced_accuracy = FALSE)
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