Azure Machine Learning Results Interpretation

Question

I try to do an experiment in Azure Machine Learning whith a "Decision Forest Regression" Algorythm to predict Weather.

I use the Weather Dataset that AML Studio suggested me (It's 400K rows of Wheater in a airport).

I would like to predict the "DryBulbCelsus" column (it's values between 20 and 23), so I select the column in the Train Model. I run it everything goes well. But the problem is that I don't understand my score model. I have 2 more colums of results "Score Label Mean" and "Score Label Standard Deviation" with data that I don't understand.

If someone work with AML and can explain me how I must interprete the data in result. Thank you !

Answer 1

Some learners, specifically the Decision Forest family and Bayes Point Machine, are capable of estimating the uncertainty around the prediction.

The "Scored Label Mean" is the prediction, and "Scored Label Standard Deviation" is the uncertainty around that prediction.