Merge pull request #111314 from Aniththa/patch-44

Update how-to-configure-auto-train.md

Author: PRMerger15

articles/machine-learning/how-to-configure-auto-train.md

@@ -451,7 +451,7 @@ To understand the scaling/normalization and algorithm/hyperparameter values for
 [('RobustScaler', RobustScaler(copy=True, quantile_range=[10, 90], with_centering=True, with_scaling=True)), ('LogisticRegression', LogisticRegression(C=0.18420699693267145, class_weight='balanced', dual=False, fit_intercept=True, intercept_scaling=1, max_iter=100, multi_class='multinomial', n_jobs=1, penalty='l2', random_state=None, solver='newton-cg', tol=0.0001, verbose=0, warm_start=False))
 ```
 
-To get more details, use this helper function shown in [this sample notebook](https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/automated-machine-learning/classification/auto-ml-classification.ipynb).
+To get more details, use this helper function: 
 
 ```python
 from pprint import pprint
@@ -471,7 +471,7 @@ def print_model(model, prefix=""):
             print()
 
 
-print_model(fitted_model)
+print_model(model)
 ```
 
 The following sample output is for a pipeline using a specific algorithm (LogisticRegression with RobustScalar, in this case).