code: def test_2_binary_no_analysis(self):
      df = pd.read_csv("tests/data/ionosphere.csv")[:100]
      mask = np.random.rand(len(df)) < 0.8
      train = df[mask]
      test = df[~mask]
      predictor = predictor_from_problem(
          df,
          ProblemDefinition.from_dict(
              {
                  "target": "target",
                  "time_aim": 20,
                  "use_default_analysis": False,
              }
          ),
      )
      predictor.learn(train)
      predictions = predictor.predict(test)
      self.assertTrue(
          balanced_accuracy_score(
              test["target"], predictions["prediction"]
          )
          > 0.5
      )
      self.assertTrue("confidence" not in predictions.columns)
  
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 4 for calling the TestBasic obj's underlying member method code with example usage: obj.test_2_binary_no_analysis() without return types