code: def fake_prob_metric(y_true, y_pred, needs_proba=True):
      return average_precision_score(y_true, y_pred)
  
file_path: skll/tests/other/custom_metrics.py
imports: from sklearn.metrics import average_precision_score, f1_score, fbeta_score, precision_score, r2_score, roc_auc_score
label_desc: Use image node_id 6 for calling a global function with example usage: fake_prob_metric(y_true, y_pred, needs_proba) and returns: average_precision_score