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An Application of Linear Programming Discriminant Analysis to Classifying and Predicting the Symptomatic Status of HIV/AIDS Patients

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Abstract

This study presents an application of linear programming discriminant analysis (LPDA) to classify and to predict the symptomatic status of HIV/AIDS patients. We applied LPDA as well as several traditional discriminant analysis methods to the AIDS Cost and Services Utilization Survey data set in order to demonstrate the use of LPDA to classify the symptomatic status of HIV/AIDS patients. The potential benefit of LPDA in terms of the classification accuracy was also analyzed.

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Authors and Affiliations

  1. Department of Decision Sciences and MIS, St. Louis University, St. Louis, Missouri, 63108

    N. K. Kwak & Seong Ho Kim

  2. Department of Business Administration, Chinju National University, Chinju, 660-758, South Korea

    Chang W. Lee

  3. School of Business and Economics, Inha University, Inchon, 402-751, South Korea

    Tae Sung Choi

Authors
  1. N. K. Kwak
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  2. Seong Ho Kim
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  3. Chang W. Lee
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  4. Tae Sung Choi
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Correspondence to N. K. Kwak.

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Kwak, N.K., Kim, S.H., Lee, C.W. et al. An Application of Linear Programming Discriminant Analysis to Classifying and Predicting the Symptomatic Status of HIV/AIDS Patients. Journal of Medical Systems 26, 427–438 (2002). https://doi.org/10.1023/A:1016496916732

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