Recognition of functional dependencies in data
Discovery of regularities in data involves search in many spaces, for instance in the space of functional expressions. If data do not fit any solution in a particular space, much time could be saved if that space was not searched at all. A test which determines the existence of a solution in a particular space, if available, can prevent unneeded search. We discuss a functionality test, which distinguishes data satisfying the functional dependence definition. The test is general and computationally simple. It permits error in data, limited number of outliers, and background noise. We show, how our functionality test works in database exploration within the 49er system as a trigger for the computationally expensive search in the space of equations. Results of tests show the savings coming from application of the test. Finally, we discuss how the functionality test can be used to recognize multifunctions.
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