class_docstr: This track evaluates a model's performance on binary classification tasks.
  These do not include synthetic datasets.
  
  Parameters
  ----------
  n_samples
      The number of samples to use for each dataset.
class_docstr_tok: ["This","track","evaluates","a","model","'s","performance","on","binary","classification","tasks",".","These","do","not","include","synthetic","datasets",".","Parameters","--","--","--","--","--","n_samples","The","number","of","samples","to","use","for","each","dataset","."]
code: def __init__(self):
      super().__init__(
          name="Binary classification",
          datasets=[
              datasets.Bananas(),
              datasets.Elec2(),
              datasets.Phishing(),
              datasets.SMTP(),
          ],
          metric=metrics.Accuracy() + metrics.F1(),
      )
  
file_path: river/river/evaluate/tracks.py
imports: from __future__ import annotations
  from river import datasets, evaluate, metrics
label_desc: Use image node_id 1 to create a new BinaryClassificationTrack object from inherited base classes: Track with example: obj = BinaryClassificationTrack()