Feature Selection Loop Start (2:2)
This node is the start of the feature selection loop. The feature selection loop allows you to select, from all the features in the input data set, the subset of features that is best for model construction. With this node you determine (i) which features/columns are to be held fixed in the selection process. These constant or "static" features/columns are included in each loop iteration and are exempt from elimination; (ii) which selection strategy is to be used on the other (variable) features/columns and its settings; and (iii) the specific settings of the selected strategy. This node has two in and out ports. The respective first port is intended for training data and the second port for test data. The same filter is applied to both tables and they will therefore always contain the same columns.
- Type: Data A data table containing all features and static columns needed for the feature selection. (Trainingdata)
- Type: Data A data table containing all features and static columns needed for the feature selection. (Testdata)
- Type: Data The input table with some columns filtered out. (Training data)
- Type: Data The input table with some columns filtered out. (Test data)
Analytics > Mining > Feature Selection
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