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Creating Insanity In Learning Systems: Addressing Ambiguity Effects Of Predicting Non-Linear Continuous Valued Functions With Reconstructabilty Analysis From Large Categorically Valued Input Data Sets, William D. Eisenhauer Dec 2009

Creating Insanity In Learning Systems: Addressing Ambiguity Effects Of Predicting Non-Linear Continuous Valued Functions With Reconstructabilty Analysis From Large Categorically Valued Input Data Sets, William D. Eisenhauer

Systems Science Friday Noon Seminar Series

Being told to give two different, and potentially counter, responses to the same stimulus can set up a double bind in humans, leading to a type of insanity. So what how do you deal with it when it comes up quite frequently in modeling through simplification and removal of predictive variables?

In his current dissertation research Ike Eisenhauer is using reconstructability analysis to implement K-System, U-System, and B-System approaches to predict a continuously valued function through discrete categorically valued input variables [e.g. textual data]. One of the key issues is how to address the inability of K-Systems and U-Systems ...