Re: Result dataset after prediction is missing all rows and no error
When designing a Machine Learning algorithm in the Visual Analysis environment of DSS, you can add steps in the "Script" tab of the analysis. All these steps are applied before the data reaches the feature preprocessing and the model training/scoring. They are also bundled when you deploy the model to the flow or to a real-time API endpoint. This is similar to the concept of scikit-learn Pipeline, if you are familiar with it. It is actually a powerful way to bundle data preparation, feature processing and model scoring in a real-time setting.