docstr: Tests if AutoML is working on a scikit-learn's pipeline
docstr_tok: ["Tests","if","AutoML","is","working","on","a","scikit-learn","'s","pipeline"]
code: def test_scikit_learn_pipeline_integration(self):
      """
      Tests if AutoML is working on a scikit-learn's pipeline
      """
      # Create dataset
      X, y = datasets.make_classification(n_samples=30)
      # apply PCA to X
      new_X = PCA(random_state=0).fit_transform(X)
      # Create default model
      default_model = AutoML(
          algorithms=["Linear"],
          random_state=0,
          results_path=self.automl_dir,
      )
      # Fit default model with transformed X and y, and predict transformed X
      y_pred_default = default_model.fit(new_X, y).predict(new_X)
  
      # Create pipeline with PCA and AutoML
      pipeline = make_pipeline(
          PCA(random_state=0),
          AutoML(algorithms=["Linear"], random_state=0),
      )
      # Fit with original X and y and predict X
      y_pred_pipe = pipeline.fit(X, y).predict(X)
      # y_pred_default must be equal to y_pred_pipe
      self.assertTrue((y_pred_pipe == y_pred_default).all())
  
imports: import os
  import unittest
  import tempfile
  import json
  import numpy
  import pandas
  import shutil
  from sklearn import datasets
  from sklearn.pipeline import make_pipeline
  from sklearn.decomposition import PCA
  from supervised import AutoML
  from supervised.exceptions import AutoMLException
label_desc: Use image node_id 8 for calling the AutoMLTest obj's underlying member method code with example usage: obj.test_scikit_learn_pipeline_integration() without return types