Merge pull request #26 from perib/patch-1

fix get_metric_score to get_metric_fn

docs/benchmark.md

@@ -150,7 +150,7 @@ First, the list of tasks is downloaded as already illustrated above. Next, a spe
 
  task = openml.tasks.get_task(task_id) # download the OpenML task
  run = openml.runs.run_model_on_task(clf, task) # run the classifier on the task
- score = run.get_metric_score(sklearn.metrics.accuracy_score) # print accuracy score
+ score = run.get_metric_fn(sklearn.metrics.accuracy_score) # print accuracy score
  print('Data set: %s; Accuracy: %0.2f' % (task.get_dataset().name,score.mean()))
  run.publish() # publish the experiment on OpenML (optional, requires internet and an API key)
  print('URL for run: %s/run/%d' %(openml.config.server,run.run_id))