Splitting & Categorical Casting | Intro to Azure ML Part 9 from ml model evaluation Watch Video
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⏲ Duration: 11 min 28 sec ✓ Published: 30-Aug-2017
Description: Before we can feed this dataset into a machine learning model there are two things we have to take care of. First we have to make sure all the categorical features are treated as categories. We’ll use the editmeta data module once again to cast these features. Then we need to setup a holdout dataset for future evaluation of any model that we build. We will randomly sample our dataset into two partitions, a training set and a test set. The test set we will lock away to pretend that its future w
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