text: from lazypredictplus.Supervised import LazyClassifier
  from sklearn.ensemble import RandomForestClassifier, ExtraTreesClassifier
  from sklearn.linear_model import SGDClassifier
  from sklearn.discriminant_analysis import (
      LinearDiscriminantAnalysis,
      QuadraticDiscriminantAnalysis,
  )
  from sklearn.model_selection import train_test_split
  from sklearn import datasets
  
  
  def main():
      # Load data
      data = datasets.load_breast_cancer()
      X, y = data.data, data.target
  
      # Split in training and testing data
      X_train, X_test, y_train, y_test = train_test_split(
          X, y, test_size=0.2, random_state=42
      )
  
      # Lazy Classifier configuration with SPECIFIC classifier algorithms
      clf = LazyClassifier(
          verbose=0,
          ignore_warnings=True,
          custom_metric=None,
          classifiers=[
              RandomForestClassifier,
              LinearDiscriminantAnalysis,
              ExtraTreesClassifier,
              QuadraticDiscriminantAnalysis,
              SGDClassifier,
          ],
      )
      # Training and testing evaluation
      models, predictions = clf.fit(X_train, X_test, y_train, y_test)
      print(models)
  
  
  if __name__ == "__main__":
      main()
  