class_docstr: Base class for Agreement metrics.
class_docstr_tok: ["Base","class","for","Agreement","metrics","."]
docstr: Args:
      annotated_dataset: Annotated dataset as expected by the metric.
      distance_function: Distance function to use for the metric.
          Depending on the type of data we need a function to compute the distance.
          For example for binary data we can use the binary distance function,
          while RatingQuestion works with an interval distance as we are dealing with
          numeric values.
docstr_tok: ["Args",":","annotated_dataset",":","Annotated","dataset","as","expected","by","the","metric",".","distance_function",":","Distance","function","to","use","for","the","metric",".","Depending","on","the","type","of","data","we","need","a","function","to","compute","the","distance",".","For","example","for","binary","data","we","can","use","the","binary","distance","function",",","while","RatingQuestion","works","with","an","interval","distance","as","we","are","dealing","with","numeric","values","."]
code: def __init__(
      self,
      annotated_dataset: FormattedResponses = None,
      distance_function: Callable = lambda x: x,
  ) -> None:
      """
      Args:
          annotated_dataset: Annotated dataset as expected by the metric.
          distance_function: Distance function to use for the metric.
              Depending on the type of data we need a function to compute the distance.
              For example for binary data we can use the binary distance function,
              while RatingQuestion works with an interval distance as we are dealing with
              numeric values.
      """
      self._dataset = annotated_dataset
      self._distance_function = distance_function
  
imports: from abc import ABC, abstractmethod
  from typing import TYPE_CHECKING, Any, Callable, Dict, Hashable, List, Tuple, Union
  import pandas
  from argilla.client.feedback.schemas.remote.shared import RemoteSchema
  from argilla.pydantic_v1 import BaseModel
label_desc: Use image node_id 1 to create a new AnnotationTaskMetricBase object from inherited base classes: ABC with example: obj = AnnotationTaskMetricBase(annotated_dataset, distance_function)