The following node is available in the Open Source KNIME predictive analytics and data mining platform version 2.7.1. Discover over 1000 other nodes, as well as enterprise functionality at http://knime.com.
This node implements the CAIM binning (discretization) algorithm according to Kurgan and Cios (2004) URL:http://citeseer.ist.psu.edu/kurgan04caim.html. The binning (discretization) is performed with respect to a selected class column. CAIM creates all possible binning boundaries and chooses those that minimize the class interdependancy measure. To reduce the runtime, this implementation creates only those boundaries where the value and the class changes. The algorithm finds a minimum number of bins (guided by the number of possible class values) and labels them "Interval_X". Only columns compatible with double values are binned and the column's type of the output table is changed to "String".
0 | The data table to bin (discretize). |
0 | The binned data table. |
1 | The model representing the binning. Contains the intervals for each bin of each column. |