Increasing sensitivity of preterm birth by changing rule strengths

Authors:
Jerzy W. Grzymala-Busse;Linda K. Goodwin;Xiaohui Zhang
Affiliations:
Department of Electrical Engineering and Computer Science, University of Kansas, Lawrence, KS;Department of Information Services and the School of Nursing, Duke University, Durham, NC;Department of Electrical Engineering and Computer Science, University of Kansas, Lawrence, KS
Venue:
Pattern Recognition Letters - Special issue: Rough sets, pattern recognition and data mining
Year:
2003

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Abstract

We studied two prenatal data sets and two other medical data sets. Our objective was to increase sensitivity (accuracy of preterm birth) by changing the rule strength for the preterm birth class. Two criteria for choosing the optimal rule strength are discussed: the greatest difference between the true-positive and false-positive probabilities and the maximum profit.