MultiLabel Classification: objectives and metrics
Objectives and metrics
MultiLogloss
where and
Usage information See more.
User-defined parameters
use_weights
Use object/group weights to calculate metrics if the specified value is true
and set all weights to 1
regardless of the input data if the specified value is false
.
Default: true
MultiCrossEntropy
where and
Usage information See more.
User-defined parameters
use_weights
Use object/group weights to calculate metrics if the specified value is true
and set all weights to 1
regardless of the input data if the specified value is false
.
Default: true
Precision
This function is calculated separately for each class k numbered from 0 to M – 1.
Can't be used for optimization. See more.
User-defined parameters
use_weights
Use object/group weights to calculate metrics if the specified value is true
and set all weights to 1
regardless of the input data if the specified value is false
.
Default: true
Recall
This function is calculated separately for each class k numbered from 0 to M – 1.
Can't be used for optimization. See more.
User-defined parameters
use_weights
Use object/group weights to calculate metrics if the specified value is true
and set all weights to 1
regardless of the input data if the specified value is false
.
Default: true
F
This function is calculated separately for each class k numbered from 0 to M – 1.
Can't be used for optimization. See more.
User-defined parameters
beta
The parameter of the F metric.
Valid values are real numbers in the following range: .
Default: This parameter is obligatory (the default value is not defined)
use_weights
Use object/group weights to calculate metrics if the specified value is true
and set all weights to 1
regardless of the input data if the specified value is false
.
Default: true
F1
This function is calculated separately for each class k numbered from 0 to M – 1.
Can't be used for optimization. See more.
User-defined parameters
use_weights
Use object/group weights to calculate metrics if the specified value is true
and set all weights to 1
regardless of the input data if the specified value is false
.
Default: true
Accuracy
The formula depends on the value of the parameter:
Classic
where
PerClass
This function is calculated separately for each class k numbered from 0 to M – 1.
Can't be used for optimization. See more.
User-defined parameters
type
The type of calculated accuracy.
Default: Classic.
Possible values: Classic, PerClass.
HammingLoss
Can't be used for optimization. See more.
User-defined parameters
use_weights
Use object/group weights to calculate metrics if the specified value is true
and set all weights to 1
regardless of the input data if the specified value is false
.
Default: true
Used for optimization
| Name | Optimization | GPU Support |
|---|---|---|
| MultiLogloss | + | + |
| MultiCrossEntropy | + | + |
| Precision | - | - |
| Recall | - | - |
| F | - | - |
| F1 | - | - |
| Accuracy | - | - |
| HammingLoss | - | - |