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RSEISP
2007
Springer

Generalizing Data in Natural Language

12 years 22 days ago
Generalizing Data in Natural Language
This paper concerns the development of a new direction in machine learning, called natural induction, which requires from computergenerated knowledge not only to have high predictive accuracy, but also to be in human-oriented forms, such as natural language descriptions and/or graphical representations. Such forms facilitate understanding and acceptance of the learned knowledge, and making mental models that are useful for decision making. An initial version of the AQ21-NI program for natural induction and its several novel features are briefly described. The performance of the program is illustrated by an example of deriving medical diagnostic rules from micro-array data.
Ryszard S. Michalski, Janusz Wojtusiak
Added 09 Jun 2010
Updated 09 Jun 2010
Type Conference
Year 2007
Where RSEISP
Authors Ryszard S. Michalski, Janusz Wojtusiak
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