Defaults
eva.metrics.BinaryClassificationMetrics
Bases: MetricCollection
Default metrics for binary classification tasks.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
threshold |
float
|
Threshold for transforming probability to binary (0,1) predictions |
0.5
|
ignore_index |
int | None
|
Specifies a target value that is ignored and does not contribute to the metric calculation. |
None
|
prefix |
str | None
|
A string to append in front of the keys of the output dict. |
None
|
postfix |
str | None
|
A string to append after the keys of the output dict. |
None
|
Source code in src/eva/core/metrics/defaults/classification/binary.py
eva.metrics.MulticlassClassificationMetrics
Bases: MetricCollection
Default metrics for multi-class classification tasks.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
num_classes |
int
|
Integer specifying the number of classes. |
required |
average |
Literal['macro', 'weighted', 'none']
|
Defines the reduction that is applied over labels. |
'macro'
|
ignore_index |
int | None
|
Specifies a target value that is ignored and does not contribute to the metric calculation. |
None
|
prefix |
str | None
|
A string to append in front of the keys of the output dict. |
None
|
postfix |
str | None
|
A string to append after the keys of the output dict. |
None
|