Learning from Order Examples

Authors:
Toshihiro Kamishima;Shotaro Akaho
Affiliations:
-;-
Venue:
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Year:
2002

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Abstract

We advocate a new learning task that deals with ordersof items, and we call this the Learning from Order Examples(LOE) task. The aim of the task is to acquire the rule thatis used for estimating the proper order of a given unordereditem set. The rule is acquired from training examples thatare ordered item sets. We present several solution methodsfor this task, and evaluate the performance and the characteristicsof these methods based on the experimental resultsof tests using both artificial data and realistic data.