Chapter 10: Training and Evaluating a Model
In the previous chapter, you familiarized yourself with a multivariate industrial water pump dataset and learned how to configure data with Amazon Lookout for Equipment. You also ingested your dataset in the service and learned about the main errors that can arise during this step.
In this chapter, you will use the datasets you prepared and ingested previously to train a multivariate anomaly detection model. You will learn how to configure your model training and the impact each parameter can have on your results. You will also develop an understanding of the key drivers that can increase your training duration. At the end of this chapter, we will walk through the evaluation and diagnostics dashboard to give you the right perspective about the quality of the outputs.
In this chapter, we're going to cover the following main topics:
- Using your dataset to train a model
- Organizing your models
- Choosing a good data split...