class_docstr: Base class for evaluation results.
  
  Args:
      samples: the :class:`fiftyone.core.collections.SampleCollection` used
      config: the :class:`fiftyone.core.evaluation.EvaluationMethodConfig`
          used
      eval_key: the evaluation key
      ytrue: a list of ground truth labels
      ypred: a list of predicted labels
      confs (None): an optional list of confidences for the predictions
      weights (None): an optional list of sample weights
      ytrue_ids (None): a list of IDs for the ground truth labels
      ypred_ids (None): a list of IDs for the predicted labels
      classes (None): the list of possible classes. If not provided, the
          observed ground truth/predicted labels are used
      missing (None): a missing label string. Any None-valued labels are
          given this label for evaluation purposes
      samples (None): the :class:`fiftyone.core.collections.SampleCollection`
          for which the results were computed
      backend (None): a :class:`fiftyone.core.evaluation.EvaluationMethod`
          backend
class_docstr_tok: ["Base","class","for","evaluation","results",".","Args",":","samples",":","the",":","class",":","`","fiftyone.core.collections.SampleCollection","`","used","config",":","the",":","class",":","`","fiftyone.core.evaluation.EvaluationMethodConfig","`","used","eval_key",":","the","evaluation","key","ytrue",":","a","list","of","ground","truth","labels","ypred",":","a","list","of","predicted","labels","confs","(","None",")",":","an","optional","list","of","confidences","for","the","predictions","weights","(","None",")",":","an","optional","list","of","sample","weights","ytrue_ids","(","None",")",":","a","list","of","IDs","for","the","ground","truth","labels","ypred_ids","(","None",")",":","a","list","of","IDs","for","the","predicted","labels","classes","(","None",")",":","the","list","of","possible","classes",".","If","not","provided",",","the","observed","ground","truth\/predicted","labels","are","used","missing","(","None",")",":","a","missing","label","string",".","Any","None-valued","labels","are","given","this","label","for","evaluation","purposes","samples","(","None",")",":","the",":","class",":","`","fiftyone.core.collections.SampleCollection","`","for","which","the","results","were","computed","backend","(","None",")",":","a",":","class",":","`","fiftyone.core.evaluation.EvaluationMethod","`","backend"]
docstr: Prints a classification report for the results via
  :func:`sklearn:sklearn.metrics.classification_report`.
  
  Args:
      classes (None): an optional list of classes to include in the
          report
      digits (2): the number of digits of precision to print
docstr_tok: ["Prints","a","classification","report","for","the","results","via",":","func",":","`","sklearn",":","sklearn.metrics.classification_report","`",".","Args",":","classes","(","None",")",":","an","optional","list","of","classes","to","include","in","the","report","digits","(","2",")",":","the","number","of","digits","of","precision","to","print"]
code: def print_report(self, classes=None, digits=2):
      """Prints a classification report for the results via
      :func:`sklearn:sklearn.metrics.classification_report`.
  
      Args:
          classes (None): an optional list of classes to include in the
              report
          digits (2): the number of digits of precision to print
      """
      labels = self._parse_classes(classes)
  
      if labels.size == 0:
          print("No classes to analyze")
          return
  
      report_str = skm.classification_report(
          self.ytrue,
          self.ypred,
          labels=labels,
          digits=digits,
          sample_weight=self.weights,
          zero_division=0,
      )
      print(report_str)
  
file_path: fiftyone/fiftyone/utils/eval/base.py
imports: import itertools
  import numpy
  import sklearn.metrics
  import fiftyone.core.evaluation
  import fiftyone.core.plots
label_desc: Use image node_id 4 for calling the BaseEvaluationResults obj's underlying member method code with example usage: obj.print_report(classes, digits) without return types