📄 zero_or_one¶

Note

ID: tasks.classification.binary.zero_or_one | Type: FormTask

{
    "augmentable_inputs": [
        "text"
    ],
    "inputs": {
        "class": "str",
        "text": "str",
        "text_type": "str"
    },
    "metrics": [
        "metrics.accuracy",
        "metrics.f1_binary"
    ],
    "outputs": {
        "class": "str",
        "label": "int"
    },
    "prediction_type": "str",
    "type": "form_task"
}

Explanation about FormTask¶

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

Attributes:

inputs (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.

outputs (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.

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

References: metrics.f1_binary, metrics.accuracy