which stopping criterion in dicretize by entropy

peppep Member Posts: 7 Contributor II
edited November 2018 in Help
The specification of the discretize by entropy operator says: "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."
Which of the stopping criteria is used in this implementation (the one based on threshold of entropy? maximum number of bins?), and how can its parameter be set please? 


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    landland RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 2,531 Unicorn
    actually I don't know myself, but the source code says, you should refer to

    a) Multi-interval discretization of continued-values attributes for classification learning (Fayyad,Irani) and
    b) Supervised and Unsupervised Discretization (Dougherty,Kohavi,Sahami).

    Tell me if you know...

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