Classification: objectives and metrics


Name	Used for optimization	User-defined parameters	Formula and/or description
Logloss	+	use_weights Default: true	Calculation principles
CrossEntropy	+	use_weights Default: true	Calculation principles
Precision	–	use_weights Default: true	Calculation principles
Recall	–	use_weights Default: true	Calculation principles
F1	–	use_weights Default: true	Calculation principles
BalancedAccuracy	–	use_weights Default: true	Calculation principles
BalancedErrorRate	–	use_weights Default: true	Calculation principles
MCC	–	use_weights Default: true	Calculation principles
Accuracy	–	use_weights Default: true	Calculation principles
CtrFactor	–	use_weights Default: true	Calculation principles
AUC*	–	use_weights Default: false type Default: “Classic” for models with Logloss and CrossEntropy loss functions and “Ranking” for models with ranking loss functions.	Classic $\text{[math]}$ The sum is calculated on all pairs of objects $\text{[math]}$ such that: $\text{[math]}$ $\text{[math]}$ $\text{[math]}$ Refer to the Wikipedia article for details. If the target type is not binary, then every object with target value $\text{[math]}$ and weight $\text{[math]}$ is replaced with two objects for the metric calculation: $\text{[math]}$ with weight $\text{[math]}$ and target value 1 $\text{[math]}$ with weight $\text{[math]}$ and target value 0. Target values must be in the range [0; 1]. Ranking $\text{[math]}$ The sum is calculated on all pairs of objects $\text{[math]}$ such that: $\text{[math]}$ $\text{[math]}$
NormalizedGini	–	use_weights Default: true	See AUC. Calculation principles
BrierScore	–	–	Calculation principles
HingeLoss	–	use_weights Default: true	Calculation principles
HammingLoss	–	use_weights Default: true	Calculation principles
ZeroOneLoss	–	use_weights Default: true	Calculation principles
Kappa	–	–	Calculation principles
WKappa	–	–	Calculation principles
LogLikelihoodOfPrediction	–	–	Calculation principles


Name	Used for optimization	User-defined parameters	Formula and/or description
Logloss	+	use_weights Default: true	Calculation principles
CrossEntropy	+	use_weights Default: true	Calculation principles
Precision	–	use_weights Default: true	Calculation principles
Recall	–	use_weights Default: true	Calculation principles
F1	–	use_weights Default: true	Calculation principles
BalancedAccuracy	–	use_weights Default: true	Calculation principles
BalancedErrorRate	–	use_weights Default: true	Calculation principles
MCC	–	use_weights Default: true	Calculation principles
Accuracy	–	use_weights Default: true	Calculation principles
CtrFactor	–	use_weights Default: true	Calculation principles
AUC*	–	use_weights Default: false type Default: “Classic” for models with Logloss and CrossEntropy loss functions and “Ranking” for models with ranking loss functions.	Classic $\text{[math]}$ The sum is calculated on all pairs of objects $\text{[math]}$ such that: $\text{[math]}$ $\text{[math]}$ $\text{[math]}$ Refer to the Wikipedia article for details. If the target type is not binary, then every object with target value $\text{[math]}$ and weight $\text{[math]}$ is replaced with two objects for the metric calculation: $\text{[math]}$ with weight $\text{[math]}$ and target value 1 $\text{[math]}$ with weight $\text{[math]}$ and target value 0. Target values must be in the range [0; 1]. Ranking $\text{[math]}$ The sum is calculated on all pairs of objects $\text{[math]}$ such that: $\text{[math]}$ $\text{[math]}$
NormalizedGini	–	use_weights Default: true	See AUC. Calculation principles
BrierScore	–	–	Calculation principles
HingeLoss	–	use_weights Default: true	Calculation principles
HammingLoss	–	use_weights Default: true	Calculation principles
ZeroOneLoss	–	use_weights Default: true	Calculation principles
Kappa	–	–	Calculation principles
WKappa	–	–	Calculation principles
LogLikelihoodOfPrediction	–	–	Calculation principles