Araştırma Makalesi
BibTex RIS Kaynak Göster

Three Group Classification Problem Approach Based on Fuzzy Goal Programming

Yıl 2020, Cilt: 23 Sayı: 4, 1089 - 1095, 01.12.2020
https://doi.org/10.2339/politeknik.600520

Öz

In this study, a
new fuzzy logic and mathematical programming based model was proposed to solve
three-group classification problem. Determination of cut-off value, which
corresponds to discrimination axis in classification problems, has importance.
Status of the cut-off value such as asymmetric triangle fuzzy number, trapezoid
fuzzy number and gauss fuzzy number was examined. The proposed approach
displayed better performance when compared to Fisher's Linear Discriminant
Function and some mathematical programming-based models by using three group
data sets used frequently in the literature. 

Kaynakça

  • [1] Fisher, R.A., “The use of multiple measurements in taxonomy problems”, Annals of Eugenics, 7, 179-188, (1936).
  • [2] Smith, C. A., “Some examples of discrimination”, Annals of Eugenics, 13(1), 272-282, (1946).
  • [3] Freed, N. & Glover, N.,”A linear programming approach to the discriminant problem”, Decision Sciences, 12, 68-74, (1981).
  • [4] Stam, A. & Ragsdale, C.T., “On the classification gap in mathematical programming-based approaches to the discriminant problem”, Naval Research Logistics, 39, 545-559, (1992).
  • [5] Rosen, J.B.,” Pattern separation by convex programming”, Journal of Mathematical Analysis and Applications, 10, 123-134, (1965).
  • [6] Mangasarian O., “Linear and Nonlinear Separation of patterns by Linear Programming”, Operations Research, 13, 444-452, (1965).
  • [7] Smith, F.W. “Pattern classifier design by linear programming”, IEEE Transactions on Computers, C-17 (4), 367-372, (1968).
  • [8] Grinold, R.C.,” Mathematical programming methods for pattern classification”, Management Sciences, 19, 272-289,(1972).
  • [9] Bajgier, S. M.& Hill, A. V.,” An experimental comparison of statistical and linear programming approaches to the discriminant problem”, Decision Sciences, 13, 604–618, (1982).
  • [10] Lam, K.F., Moy, J.W., “An experimental comparison of some recently developed linear programming approaches to the discriminant analysis”, Computers and Operations Research, 24(7), 593-599, (1997).
  • [11] Glen, J. J.,” Integer programming methods for normalisation and variable selection in mathematical programming discriminant analysis models”, Journal of Operational Research Society, 50, 1043–1053, (1999).
  • [12] Lam, K.F., Choo, E.U., Moy, J.W.,” Minimizing deviations from the group mean: A new linear programming approach for the two-group classification problem”, European Journal of Operational Research, 88,358-367, (1996).
  • [13] Bal, H., Örkcü, H.H., Çelebioğlu S., “An alternative model to Fisher linear programming approaches in two-group classification problem: Minimizing deviations from the group median”, G.U. Journal of Science, 19(1): 49–55 (2006).
  • [14] Bal, H., Örkcü, H.H., Çelebioğlu S., “An experimental comparison of the new goal programming and linear programming approaches in the two-group discriminant problems”, Computers&Industrial Engineering, 50(3): 296–311 (2006).
  • [15] Gehrlein, W.V., ”General mathematical programming formulations for the statistical classification problem”, Operations Research Letters, 5,299-304, (1986).
  • [16] Choo, E.U., Wedley, W.C., “Optimal criterion weights in repetitive multicriteria decision making”, Journal of Operational Research Society, 36: 983-992, (1985).
  • [17] Lam, K.F., Moy, J.W., “Improved linear programming formulations for the multi group discriminant problem”, Journal of Operational Research Society, 47: 1526-1529 (1996).
  • [18] Lam, K.F., Choo, E.U., Moy, J.W., "Minimizing deviations from the group mean: A new linear programming approach for the two-group classification problem", European Journal of Operational Research, 88,358-367, (1996).
  • [19] Örkcü, H. H., & Bal, H., “A combining mathematical programming method for multi-group data classification”, Gazi University Journal of Science, 24(1), 77–84, (2011).
  • [20] Youssef, S. B., Jbir, R., & Rebai, A., “A three-group discrimination using new linear programming model”, International Journal of Operational Research, 12(3), 279-293, (2011).
  • [21] Smaoui, S. & Aouni, B.,” Fuzzy goal programming model for classification problems”, Ann Oper Res, 251:141–160, (2017).
  • [22] Doğan, M. I., Orman, A., Örkcü, M., & Örkcü, H. H., “A new approach based on regression analysis and mathematical programming to multi-group classification problems”, Journal Of The Faculty Of Engıneering And Architecture Of Gazi University, 34(4), 1939-1955, (2019).
  • [23] Zadeh, L.A., “Fuzzy Sets”, Information and Control, 8 (3), 338-353, (1965).
  • [24] Narasimhan, R., “Goal programming in a fuzzy environment”, Decision sciences, 11(2), 325-336, (1980).
  • [25] Hannan, E. L., “On fuzzy goal programming”, Decision sciences, 12(3), 522-531, (1981).
  • [26] Li, A., Shi, Y., & He, J., “A data classification method based on fuzzy linear programming”, In MCDM 2006, Chania, Greece, July 19–23, (2006).
  • [27] Hosseinzadeh, L. F., Jahanshahloo, G. R., Rezai, B. F., & Zhiani, R. H., “Discriminant analysis of imprecise data”, Applied Mathematical Sciences, 1(15), 723–737, (2007).
  • [28] Hosseinzadeh, L. F., & Mansouri, B.,”The extended data Envelopment analysis/discriminant analysis approach of fuzzy models”, Applied Mathematical Sciences, 2(30), 1465–1477, (2008).
  • [29] Ben Youssef, S., & Rebai, A., “Discriminant analysis using linear programming models”, International Journal of Knowledge Management Studies, 2(4), 455–459, (2008).

Three Group Classification Problem Approach Based on Fuzzy Goal Programming

Yıl 2020, Cilt: 23 Sayı: 4, 1089 - 1095, 01.12.2020
https://doi.org/10.2339/politeknik.600520

Öz

In this study, a
new fuzzy logic and mathematical programming based model was proposed to solve
three-group classification problem. Determination of cut-off value, which
corresponds to discrimination axis in classification problems, has importance.
Status of the cut-off value such as asymmetric triangle fuzzy number, trapezoid
fuzzy number and gauss fuzzy number was examined. The proposed approach
displayed better performance when compared to Fisher's Linear Discriminant
Function and some mathematical programming-based models by using three group
data sets used frequently in the literature. 

Kaynakça

  • [1] Fisher, R.A., “The use of multiple measurements in taxonomy problems”, Annals of Eugenics, 7, 179-188, (1936).
  • [2] Smith, C. A., “Some examples of discrimination”, Annals of Eugenics, 13(1), 272-282, (1946).
  • [3] Freed, N. & Glover, N.,”A linear programming approach to the discriminant problem”, Decision Sciences, 12, 68-74, (1981).
  • [4] Stam, A. & Ragsdale, C.T., “On the classification gap in mathematical programming-based approaches to the discriminant problem”, Naval Research Logistics, 39, 545-559, (1992).
  • [5] Rosen, J.B.,” Pattern separation by convex programming”, Journal of Mathematical Analysis and Applications, 10, 123-134, (1965).
  • [6] Mangasarian O., “Linear and Nonlinear Separation of patterns by Linear Programming”, Operations Research, 13, 444-452, (1965).
  • [7] Smith, F.W. “Pattern classifier design by linear programming”, IEEE Transactions on Computers, C-17 (4), 367-372, (1968).
  • [8] Grinold, R.C.,” Mathematical programming methods for pattern classification”, Management Sciences, 19, 272-289,(1972).
  • [9] Bajgier, S. M.& Hill, A. V.,” An experimental comparison of statistical and linear programming approaches to the discriminant problem”, Decision Sciences, 13, 604–618, (1982).
  • [10] Lam, K.F., Moy, J.W., “An experimental comparison of some recently developed linear programming approaches to the discriminant analysis”, Computers and Operations Research, 24(7), 593-599, (1997).
  • [11] Glen, J. J.,” Integer programming methods for normalisation and variable selection in mathematical programming discriminant analysis models”, Journal of Operational Research Society, 50, 1043–1053, (1999).
  • [12] Lam, K.F., Choo, E.U., Moy, J.W.,” Minimizing deviations from the group mean: A new linear programming approach for the two-group classification problem”, European Journal of Operational Research, 88,358-367, (1996).
  • [13] Bal, H., Örkcü, H.H., Çelebioğlu S., “An alternative model to Fisher linear programming approaches in two-group classification problem: Minimizing deviations from the group median”, G.U. Journal of Science, 19(1): 49–55 (2006).
  • [14] Bal, H., Örkcü, H.H., Çelebioğlu S., “An experimental comparison of the new goal programming and linear programming approaches in the two-group discriminant problems”, Computers&Industrial Engineering, 50(3): 296–311 (2006).
  • [15] Gehrlein, W.V., ”General mathematical programming formulations for the statistical classification problem”, Operations Research Letters, 5,299-304, (1986).
  • [16] Choo, E.U., Wedley, W.C., “Optimal criterion weights in repetitive multicriteria decision making”, Journal of Operational Research Society, 36: 983-992, (1985).
  • [17] Lam, K.F., Moy, J.W., “Improved linear programming formulations for the multi group discriminant problem”, Journal of Operational Research Society, 47: 1526-1529 (1996).
  • [18] Lam, K.F., Choo, E.U., Moy, J.W., "Minimizing deviations from the group mean: A new linear programming approach for the two-group classification problem", European Journal of Operational Research, 88,358-367, (1996).
  • [19] Örkcü, H. H., & Bal, H., “A combining mathematical programming method for multi-group data classification”, Gazi University Journal of Science, 24(1), 77–84, (2011).
  • [20] Youssef, S. B., Jbir, R., & Rebai, A., “A three-group discrimination using new linear programming model”, International Journal of Operational Research, 12(3), 279-293, (2011).
  • [21] Smaoui, S. & Aouni, B.,” Fuzzy goal programming model for classification problems”, Ann Oper Res, 251:141–160, (2017).
  • [22] Doğan, M. I., Orman, A., Örkcü, M., & Örkcü, H. H., “A new approach based on regression analysis and mathematical programming to multi-group classification problems”, Journal Of The Faculty Of Engıneering And Architecture Of Gazi University, 34(4), 1939-1955, (2019).
  • [23] Zadeh, L.A., “Fuzzy Sets”, Information and Control, 8 (3), 338-353, (1965).
  • [24] Narasimhan, R., “Goal programming in a fuzzy environment”, Decision sciences, 11(2), 325-336, (1980).
  • [25] Hannan, E. L., “On fuzzy goal programming”, Decision sciences, 12(3), 522-531, (1981).
  • [26] Li, A., Shi, Y., & He, J., “A data classification method based on fuzzy linear programming”, In MCDM 2006, Chania, Greece, July 19–23, (2006).
  • [27] Hosseinzadeh, L. F., Jahanshahloo, G. R., Rezai, B. F., & Zhiani, R. H., “Discriminant analysis of imprecise data”, Applied Mathematical Sciences, 1(15), 723–737, (2007).
  • [28] Hosseinzadeh, L. F., & Mansouri, B.,”The extended data Envelopment analysis/discriminant analysis approach of fuzzy models”, Applied Mathematical Sciences, 2(30), 1465–1477, (2008).
  • [29] Ben Youssef, S., & Rebai, A., “Discriminant analysis using linear programming models”, International Journal of Knowledge Management Studies, 2(4), 455–459, (2008).
Toplam 29 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Araştırma Makalesi
Yazarlar

Zülal Tüzüner 0000-0003-1085-9399

Hasan Bal 0000-0003-0570-8609

Yayımlanma Tarihi 1 Aralık 2020
Gönderilme Tarihi 2 Ağustos 2019
Yayımlandığı Sayı Yıl 2020 Cilt: 23 Sayı: 4

Kaynak Göster

APA Tüzüner, Z., & Bal, H. (2020). Three Group Classification Problem Approach Based on Fuzzy Goal Programming. Politeknik Dergisi, 23(4), 1089-1095. https://doi.org/10.2339/politeknik.600520
AMA Tüzüner Z, Bal H. Three Group Classification Problem Approach Based on Fuzzy Goal Programming. Politeknik Dergisi. Aralık 2020;23(4):1089-1095. doi:10.2339/politeknik.600520
Chicago Tüzüner, Zülal, ve Hasan Bal. “Three Group Classification Problem Approach Based on Fuzzy Goal Programming”. Politeknik Dergisi 23, sy. 4 (Aralık 2020): 1089-95. https://doi.org/10.2339/politeknik.600520.
EndNote Tüzüner Z, Bal H (01 Aralık 2020) Three Group Classification Problem Approach Based on Fuzzy Goal Programming. Politeknik Dergisi 23 4 1089–1095.
IEEE Z. Tüzüner ve H. Bal, “Three Group Classification Problem Approach Based on Fuzzy Goal Programming”, Politeknik Dergisi, c. 23, sy. 4, ss. 1089–1095, 2020, doi: 10.2339/politeknik.600520.
ISNAD Tüzüner, Zülal - Bal, Hasan. “Three Group Classification Problem Approach Based on Fuzzy Goal Programming”. Politeknik Dergisi 23/4 (Aralık 2020), 1089-1095. https://doi.org/10.2339/politeknik.600520.
JAMA Tüzüner Z, Bal H. Three Group Classification Problem Approach Based on Fuzzy Goal Programming. Politeknik Dergisi. 2020;23:1089–1095.
MLA Tüzüner, Zülal ve Hasan Bal. “Three Group Classification Problem Approach Based on Fuzzy Goal Programming”. Politeknik Dergisi, c. 23, sy. 4, 2020, ss. 1089-95, doi:10.2339/politeknik.600520.
Vancouver Tüzüner Z, Bal H. Three Group Classification Problem Approach Based on Fuzzy Goal Programming. Politeknik Dergisi. 2020;23(4):1089-95.
 
TARANDIĞIMIZ DİZİNLER (ABSTRACTING / INDEXING)
181341319013191 13189 13187 13188 18016

download Bu eser Creative Commons Atıf-AynıLisanslaPaylaş 4.0 Uluslararası ile lisanslanmıştır.