Discretize by Entropy


Synopsis

Discretizes numerical attributes. Bin boundaries are chosen as to minimize the entropy in the induced partitions.


Description

This operator discretizes all numeric attributes in the dataset into nominal attributes. The discretization is performed by selecting a bin boundary minimizing the entropy in the induced partitions. The method is then applied recursively for both new partitions until the stopping criterion is reached. For Details see a) Multi-interval discretization of continued-values attributes for classification learning (Fayyad,Irani) and b) Supervised and Unsupervised Discretization (Dougherty,Kohavi,Sahami). Skips all special attributes including the label.

Please note that this operator automatically removes all attributes with only one range (i.e. those attributes which are not actually discretized since the entropy criterion is not fulfilled). This behavior can be controlled by the remove_useless parameter.


Input

, Example set matching at least one selected attribute.


Output


Parameters


ExampleProcess