Java Deep Learning Cookbook

How it works...

All features and labels need to be added to the schema as mentioned in step 1 and step 2. If we don't do that, then DataVec will throw runtime errors during data extraction/loading.

In the preceding screenshot, the runtime exception is thrown by DataVec because of unmatched count of features. This will happen if we provide a different value for input neurons instead of the actual count of features in the dataset.

From the error description, it is clear that we have only added 13 features in the schema, which ended in a runtime error during execution. The first three features, named Rownumber, Customerid, and Surname, are to ...