When building a predictive model, if many data fields are available to use as inputs to the model, then reducing the number of inputs can lead to better, simpler and easier-to-use models. Fields or features can be selected in a number of ways: by using business and data knowledge, by analysis to select individual fields that have a relation to the predictive target, and by using other models to select features whose relevance is more multivariate in nature.
In a Modeler stream, selections of fields are usually represented by Filter nodes. If multiple selections from the same set of fields have been produced, for example by generating Filter nodes from different models, then it is useful to combine these filters. Filters can be combined in different ways; for example, if we wish to select only the fields that were selected by both models, then the filters are placed in sequence. If we wish to select all the fields that were selected by either model, then a different...