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Learning qualitative models from numerical data
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DOI：10.1016/j.artint.2011.02.004.png)
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Qualitative models describe relations between the observed quantities in qualitative terms. In predictive modelling, a qualitative model tells whether the output increases or decreases with the input. We describe Pale, a new method for qualitative learning which estimates partial derivatives of the target function from training data and uses them to induce qualitative models of the target function. We formulated three methods for computation of derivatives, all based on using linear regression on local neighbourhoods. The methods were empirically tested on artificial and real-world data. We also provide a case study which shows how the developed methods can be used in practice. (C) 2011 Elsevier B.V. All rights reserved.
Keyword:
Qualitative modelling
Regression
Partial derivatives
Monotone models
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