Q: Azure Machine Learning - Empty score results I've trained a model, the test results on test-set are okay.
Now I have saved the model as 'Trained model' and made a new experiment into a new dataset, for making predictions where I don't have the actual value's. 
Normally, the trained model gives me a scored label result per instance. 
But now, the scored label results are empty. Also when I convert the score results to CSV the scored labels column is empty.
Even stranger, when I take a look at the Statistics of the score Visualize tab, I DO see the statistics of the scored values. But no actual scored values... 

Is this a bug? Or am I forgetting something important? Whats going on ;) ?

A: If your test dataset is missing the dependent values, your predictive experiment may fail for some models. The solution is to pad your csv file with zero values instead of blank values.

A: I had this same issue and it was frustrating but I think I finally understand why this is happening.
When I was training my experiment, part of the cleaning process was populating missing values or trimming existing data with R.
The problem is if one of those features is optional. For instance if you have a column that is not filled in, the scoring model will fail in the web service.
To see if this problem affects you, go to your Predictive Experiment and visualize the Score Model results. If you see empty Predicted Label & Predicted Score values, you can easily see which data points are missing.
