Toward the Integration of Exploration and Modeling in a Planning Framework

Statistical operations are often facilitated by other operations. We can facilitate modeling operations by testing their input for irregularities and removing problems wherever possible. A planning representation is well-suited to this task. We describe the representation used in Igor, a system for exploratory data analysis, and its integration with two modeling systems, Pearl's IC and Cohen's FBD. We show that introducing outliers into the inputs of the algorithms can in uence their performance. We demonstrate that a planning representation o ers a exible way of integrating outlier detection and removal into the modeling process, taking account of speci c characteristics of the modeling operations involved. This work is supported by ARPA/Rome Laboratory under contract #'s F30602-91-C-0076 and F30602-93-C-0100. To appear in Proceedings of AAAI-94 Workshop on Knowledge Discovery in Databases.