data science in the cloud with microsoft azure machine learning and r by Anthony Gray

Author:Anthony Gray
Language: eng
Format: epub
Publisher: O'Reilly Media, Inc.
Published: 2014-12-15T05:00:00+00:00

Figure 18. Azure ML Studio with first bike demand model

There are quite a few new modules on the canvas at this point.

We added a Split module after the Transform Data Execute R Script module. The subselected data are then sampled into training and test (evaluation) sets with a 70%/30% split. Ideally, we should introduce another split to make separate test and evaluation datasets. The test dataset is used for performing model parameter tuning and feature selection. The evaluation dataset is used for final performance evaluation. For the sake of simplifying our discussion here, we will not perform this additional split.

Note that we have placed the Project Columns module after the Split module so we can prune the features we’re using without affecting the model evaluation. We use the Project Columns module to select the following columns of transformed data for the model:

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