- Lastly I will compute the accuracy of each model and check how they perform on the test data.
- I will use wine quality data set from the UCI Machine Learning Repository .
- On test data, Boosted Tree had a better accuracy.
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@MikeTamir: “Predicting Wine Quality with Azure ML and R #MachineLearning #DataScience”
by Shaheen Gauher, PhD, Data Scientist at Microsoft In machine learning, the problem of classification entails correctly identifying to which class or group a new observation belongs, by learning from observations whose classes are already known. In what follows, I will build a classification experiment in Azure ML Studio to predict wine quality based on physicochemical data. Several classification algorithms will be applied on the data set and the performance of these algorithms will be compared. I will also present a tutorial on how to do similar exercise using MRS (Microsoft R Server, formerly Revolution R Enterprise). I will use…
Predicting Wine Quality with Azure ML and R