Hitchhikers Guide to Azure Machine Learning Studio
Learn Azure ML Studio through this brief hands-on tutorial. This step-by-step guide will help you get a quick-start and grasp the basics of this Predictive Modeling tool.
What is Decision Trees?
In simple words, it finds a probability of happening of an event by making trees. More details about the algorithm can be read here.
Now is the time when I would tell you that the other node of Split Column that would be the test data would go into the right hand side node of Score Model and at the left hand side, we would connect train model.
Run the model and wait until you find green ticker signs at the modules. Once it is done, right click on Score Model and visualize it. You would find two more column names at the end, One with Score Labels and other with Scored Probabilities.
By the results, and comparison of it with the original income column, we can see that our model has done pretty well but is there a way to evaluate it?
Let’s move on.
Drag the Evaluate Module and connect it with Score Model. Once again run the model and when the ticker is green, right click on Evaluate model and visualize the results.
Here our model accuracy is about 91% which means our model is doing pretty well. We can see the precision, F-measure, Recall and other results here.
Continued on next page ...
In simple words, it finds a probability of happening of an event by making trees. More details about the algorithm can be read here.
Now is the time when I would tell you that the other node of Split Column that would be the test data would go into the right hand side node of Score Model and at the left hand side, we would connect train model.
Run the model and wait until you find green ticker signs at the modules. Once it is done, right click on Score Model and visualize it. You would find two more column names at the end, One with Score Labels and other with Scored Probabilities.
By the results, and comparison of it with the original income column, we can see that our model has done pretty well but is there a way to evaluate it?
Let’s move on.
Drag the Evaluate Module and connect it with Score Model. Once again run the model and when the ticker is green, right click on Evaluate model and visualize the results.
Here our model accuracy is about 91% which means our model is doing pretty well. We can see the precision, F-measure, Recall and other results here.
Continued on next page ...
