code: def test_0_binary(self):
      df = pd.read_csv("tests/data/ionosphere.csv")[:100]
      target = "target"
      predictor = self.setup_predictor(df, target)
      predictions = predictor.predict(df)
      acc = balanced_accuracy_score(
          df[target], predictions["prediction"]
      )
      self.assertTrue(acc > 0.5)
      self.assertTrue(
          all([0 <= p <= 1 for p in predictions["confidence"]])
      )
  
file_path: lightwood/tests/integration/basic/test_categorical.py
imports: import unittest
  import numpy
  import pandas
  from sklearn.metrics import balanced_accuracy_score
  from lightwood.api.types import ProblemDefinition
  from lightwood.api.high_level import predictor_from_problem
label_desc: Use image node_id 2 for calling the TestBasic obj's underlying member method code with example usage: obj.test_0_binary() without return types