title: How to revise this code for implementing Smote Oversampling and Cross Validation pipeline to multiclass classification problem?
body: <pre><code>imba_pipeline = make_pipeline(SMOTE(random_state=42), 
                                DecisionTreeClassifier())
  cross_val_score(imba_pipeline, X_train1, y_train1, scoring='recall', cv=kf)
  </code></pre>
  <p>When I run this, it gives below error:</p>
  <p>ValueError: Target is multiclass but average='binary'. Please choose another average setting, one of [None, 'micro', 'macro', 'weighted'].</p>
  <pre><code>    Out[102]:
      array([nan, nan, nan, nan, nan])
  </code></pre>