Preparing and validating a model
In Chapter 1, we discovered some of the concepts for model validation and preparation. Qlik AutoML handles model selection automatically and provides us with comprehensive information to support the validation. We will consider model selection and validation in more detail in Chapter 7 and Qlik AutoML in Chapter 8. In this section, we will prepare for these chapters by summarizing the most important steps of model preparation and validation in Qlik. The following steps are written on Qlik AutoML point of view. When using the Advanced Analytics integration there might be small differences based on the selected technology (ie. R, Python, Azure ML Studio, AWS SageMaker, etc.).
General validation and preparation steps include the following:
- Data preparation: Start by preparing your data for machine learning. Load your data into Qlik Sense, clean and preprocess it, handle missing values, and perform feature engineering if necessary. Qlik AutoML...
