Data mining problems may involve hundreds, or even thousands, of fields that can potentially be used as inputs. As a result, a great deal of time and effort may be spent examining which fields or variables to include in the model. To narrow down the choices, the Feature Selection algorithm can be used to identify the fields that are most important for a given analysis.
- For more information about this node, see Feature Selection Overview.
- For more information about the visualizations for this node, see Feature Selection Visualizations.
Like your visualization? Why not deploy it? For more information, see Deploy a model.