Validation

Validation of a forecast model involves training the model with a portion of data (referred to as your training data) and then testing the model with a different portion (referred to as your test data).

For forecasting tasks, the training data is a prefix of the data and the test data is a suffix of the data that is withheld to compare against the forecasts.

Validating a trained model with the test set can be performed several ways, depending on the type of model. Each assistant provides methods in the Validate section, which is displayed after you train a model.

Get Implementing Splunk 7 - Third Edition now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.