Managing training data for Watson OpenScale

Preparing training data

The format of your training data can determine the results of your model evaluations. To enable model evaluations, you must prepare to store your training data in a format that Watson OpenScale can process. Your training data must contain labeled feature columns and a prediction column as shown in the following example:

Watson OpenScale uses the training data that you provide to create a training data schema to ensure that your training data corresponds with the format that it understands. The schema specifies the feature columns that you provide in your training data and the type of data that the columns contain. The following example shows a training data schema for the German Credit Risk dataset:

Storing training data

You can store your training data in Cloud Object Storage or Db2 so that you can connect your training data to Watson OpenScale.

For more information about storing your training data in Db2, see Working with integrated IBM Db2 databases.

For more information about storing your training data in Cloud Object Storage, see Getting started with IBM Cloud Object Storage.

If you want to keep the details of your training data location private, you can also connect Watson OpenScale to your training data by running a custom notebook to upload the configuration file that it generates.

Next steps

You must connect your training data to Watson OpenScale so that it understands how to process your model.

Parent topic: Managing data for model evaluations in Watson OpenScale