class |
ObservedAccuracy |
The Observed Accuracy is the fraction of predictions that include the
true label in their label set.
|
class |
ObservedExcessCriterion |
The OE/Observed Excess criterion is an observed efficiency measure based on
the number of false labels in the label set.
|
class |
ObservedFuzzinessCriterion |
The OF/Observed Fuzziness criterion is a prior efficiency measure based on
the sum of all p-values for false labels.
|
class |
ObservedMultipleCriterion |
The OM/Observed Multiple criterion is an observed efficiency measure based on
the number of false labels in the label set.
|
class |
ObservedOneCCriterion |
The Observed OneC criterion is the fraction of predictions that only have
the true label in their label set.
|
class |
ObservedProbabilityLogLoss |
The observed log loss measure depends on the prediction made and the true label.
|
class |
ObservedProbabilitySquareLoss |
The observed square loss measure depends on the prediction made and the true label.
|
class |
ObservedUnconfidenceCriterion |
The UO/Observed Unconfidence criterion is a prior efficiency measure based
on the (un)confidence of the point prediction.
|