📄 Multi Label¶

tasks.classification.multi_label

type: Task
input_fields: 
  text: str
  text_type: str
  classes: List[str]
  type_of_classes: str
reference_fields: 
  labels: List[str]
prediction_type: List[str]
metrics: 
  - metrics.f1_micro_multi_label
  - metrics.accuracy
  - metrics.f1_macro_multi_label
augmentable_inputs: 
  - text
defaults: 
  text_type: text
[source]

Explanation about Task¶

Task packs the different instance fields into dictionaries by their roles in the task.

Attributes:

input_fields (Union[Dict[str, str], List[str]]):
Dictionary with string names of instance input fields and types of respective values. In case a list is passed, each type will be assumed to be Any.

reference_fields (Union[Dict[str, str], List[str]]):
Dictionary with string names of instance output fields and types of respective values. In case a list is passed, each type will be assumed to be Any.

metrics (List[str]): List of names of metrics to be used in the task. prediction_type (Optional[str]):

Need to be consistent with all used metrics. Defaults to None, which means that it will be set to Any.

defaults (Optional[Dict[str, Any]]):
An optional dictionary with default values for chosen input/output keys. Needs to be consistent with names and types provided in ‘input_fields’ and/or ‘output_fields’ arguments. Will not overwrite values if already provided in a given instance.

The output instance contains three fields:
“input_fields” whose value is a sub-dictionary of the input instance, consisting of all the fields listed in Arg ‘input_fields’. “reference_fields” – for the fields listed in Arg “reference_fields”. “metrics” – to contain the value of Arg ‘metrics’

References: metrics.f1_micro_multi_label, metrics.f1_macro_multi_label, metrics.accuracy