Brian;
I see nothing in the
Algorithms manual that directly (or even indirectly as far as I can tell!) answers your question, but I am by no means a domain expert.
However, the manual has these references; perhaps they will be of some help to you.
Fayyad, U., and K. Irani. 1993. Multi-interval discretization of continuous-value attributes for classification learning. In: Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, San Mateo, CA: Morgan Kaufmann, 1022–1027.
Dougherty, J., R. Kohavi, and M. Sahami. 1995. Supervised and unsupervised discretization of continuous features. In: Proceedings of the Twelfth International Conference on Machine Learning, Los Altos, CA: Morgan Kaufmann, 194–202.
Liu, H., F. Hussain, C. L. Tan, and M. Dash. 2002. Discretization: An Enabling Technique. Data Mining and Knowledge Discovery, 6, 393–423.
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Rick Marcantonio
Quality Assurance
IBM
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Original Message:
Sent: Fri February 04, 2022 08:48 AM
From: Brian Joy
Subject: Optimal Binning MDLP Method
Hello all,
I am using the MPLP Method of the Optimal Binning command and am curious to know if there is any documentation around how this command would handle optimization if the variable to be binned and the guide variable do not have a relationship to one another? For example if both values of a binary guide variable had the same mean, standard dev, and distribution of the binned variable.
Thanks for you help!
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Brian Joy
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