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A procedure for meaningful unsupervised clustering and its application for solvent classification

  • Research Article
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Central European Journal of Chemistry

Abstract

Artificial neural networks have proven to be a powerful tool for solving classification problems. Some difficulties still need to be overcome for their successful application to chemical data. The use of supervised neural networks implies the initial distribution of patterns between the pre-determined classes, while attribution of objects to the classes may be uncertain. Unsupervised neural networks are free from this problem, but do not always reveal the real structure of data. Classification algorithms which do not require a priori information about the distribution of patterns between the pre-determined classes and provide meaningful results are of special interest. This paper presents an approach based on the combination of Kohonen and probabilistic networks which enables the determination of the number of classes and the reliable classification of objects. This is illustrated for a set of 76 solvents based on nine characteristics. The resulting classification is chemically interpretable. The approach proved to be also applicable in a different field, namely in examining the solubility of C60 fullerene. The solvents belonging to the same group demonstrate similar abilities to dissolve C60. This makes it possible to estimate the solubility of fullerenes in solvents for which there are no experimental data

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References

  1. Yu. Vlasov, A. Legin, A. Rudnitskaya, C. Di Natale, A. D’Amico, Pure Appl. Chem. 77, 1965 (2005)

    Article  CAS  Google Scholar 

  2. W. A. Hardcastle, Qualitative analysis: a guide to best practice (Royal Society of Chemistry, Cambridge, 1998)

    Google Scholar 

  3. B. L. Milman, Trends Anal. Chem. 24, 493 (2005)

    Article  CAS  Google Scholar 

  4. M. J. Adams, Chemometrics in analytical spectroscopy, 2nd edition (Royal Society of Chemistry, Cambridge, 2004)

    Google Scholar 

  5. Ph. K. Hopke, Anal. Chim. Acta. 500, 365 (2003)

    Article  CAS  Google Scholar 

  6. E. F. Boffo, L.A. Tavares, A.C.T. Tobias, M.M.C. Ferreira, A.G. Ferreira, Food Sci. Technol. 49, 55 (2012)

    CAS  Google Scholar 

  7. S. S. Souza, A.G. Cruz, E.H.M. Walter, J.A.F. Faria, R.M.S. Celeghini, M.M.C. Ferreira, D. Granato, A. de S. Sant’Ana, Food Chem. 124, 692 (2011)

    Article  CAS  Google Scholar 

  8. P. K. Shivaswamy, T. Jebara, J. Mach. Learn. Res. 11, 747 (2010)

    Google Scholar 

  9. R. Wehrens, Chemometrics with R: multivariate data analysis in the natural sciences and life sciences (Springer, Heidelberg, Dordrecht, London, New York, 2011)

    Book  Google Scholar 

  10. A. de Juan, G. Fonrodona, E. Casassas, Trends Anal. Chem. 16, 52 (1997)

    Article  Google Scholar 

  11. P. Gramatica, N. Navas, R. Todeschini, Trends Anal. Chem. 18, 461 (1999)

    Article  CAS  Google Scholar 

  12. V. Simeonov, P. Simeonova, S. Tsakovskii, V. Lovchinov, J. Water Resource Protect. 2, 353 (2010)

    Article  CAS  Google Scholar 

  13. R. Skorek, M. Jablonska, M. Polowniak, A. Kita, P. Janoska, F. Buhl, Cent. Eur. J. Chem. 10, 71 (2010)

    Article  Google Scholar 

  14. J. S. dos Santos, N.S. dos Santos, M.L.P. dos Santos, S.N. dos Santos, J.J. de Jesus Lacerda, J. Braz. Chem. Soc. 19, 502 (2008)

    Article  Google Scholar 

  15. R. M. Balabin, R.Z. Safieva, E.I. Lomakina, Anal. Chim. Acta 671, 27 (2010)

    Article  CAS  Google Scholar 

  16. R. M. Alonso-Salces, C. Herrero, A. Barranco, L.A. Berrueta, B. Gallo, F. Vicente, Food Chem. 93, 113 (2005)

    Article  CAS  Google Scholar 

  17. P. H. Fidencio, I. Ruisanchez, R.J. Poppi, Analyst 126, 2194 (2001)

    Article  CAS  Google Scholar 

  18. R. M. Balabin, R.Z. Safieva, Fuel. 87, 2745 (2008)

    Article  CAS  Google Scholar 

  19. O. F. Galao, D. Borsato, J.P. Pinto, J.V. Visentainer, M.C. Carrao-Panizzi, J. Braz. Chem. Soc. 22, 142 (2011)

    Article  CAS  Google Scholar 

  20. Y. Marcus, Chem. Soc. Rev. 22, 409 (1993)

    Article  CAS  Google Scholar 

  21. Ch. Reichardt, Solvents and solvent effects in organic chemistry, 3rd edition (Wiley & Co. KGaA, Weinhem, 2003)

    Google Scholar 

  22. V. J. Barwick, Trends Anal. Chem. 16, 293 (1998)

    Google Scholar 

  23. F. Marini, J. Zupan, A.L. Magri, Anal. Chim. Acta 544, 306 (2005)

    Article  CAS  Google Scholar 

  24. J. Zupan, M. Novic, I. Ruisanchez, Chemometr. Intell. Lab. 38, 1 (1997)

    Article  CAS  Google Scholar 

  25. C. Fyfe, Artificial neural networks (Department of Computing and Information Systems, University of Paisley, Scotland, 1996)

    Google Scholar 

  26. W. J. Melssen, J.R.M. Smits, L.M.C. Buydens, G. Kateman, Chemometr. Intell. Lab. 23, 267 (1994)

    Article  CAS  Google Scholar 

  27. D. Anderson, G. McNeill, Artificial neural networks technology (Kaman Sciences Corporation, New York, 1992)

    Google Scholar 

  28. M. M. Gupta, L. Jin, N. Homma, Static and dynamic neural networks: from fundamentals to advanced theory (Wiley & Sons, New Jersey, 2003)

    Book  Google Scholar 

  29. W. Tylmon, G.J. Anders, Energy 31, 2874 (2006)

    Article  Google Scholar 

  30. Y. Marcus, J. Phys. Chem. B 101, 8617 (1997)

    Article  CAS  Google Scholar 

  31. R. A. van den Berg, H.C.J. Hoefsloot, J.A. Westerhuis, A.K. Smilde, M.J. van der Werf, BMC Genomics 7, 142 (2006)

    Article  Google Scholar 

  32. K. R. Beebe, J.P. Randy, M.B. Seasholtz, Chemometrics: a practical guide (Wiley & Sons, USA, 1998)

    Google Scholar 

  33. M. Dong, N. Wang, Appl. Math. Model. 35, 1024 (2011)

    Article  Google Scholar 

  34. V. J. Barwick, Trends Anal. Chem. 16, 293 (1997)

    Article  CAS  Google Scholar 

  35. M. Chastrette, M. Rajzmann, M. Chanon, K.F. Purcell, J. Am. Chem. Soc. 107, 1 (1985)

    Article  CAS  Google Scholar 

  36. A. R. Katritzky, T. Tamm, Y. Wang, M. Karelson, J. Chem. Inf. Comput. Sci. 39, 692 (1999)

    Article  CAS  Google Scholar 

  37. A. R. Katritzky, D.C. Fara, M. Kuanar, E. Hur, M. Karelson, J. Phys. Chem. A 109, 10323 (2005)

    Article  CAS  Google Scholar 

  38. Y. Marcus, The properties of solvents. Wiley Series in Solution Chemistry (Wiley, Chichester, 1998) Vol. Vol. 4

  39. K. N. Semenov, N.A. Charykov, V.A. Keskinov, A.K. Piartman, A.A. Blokhin, A.A. Kopyrin, J. Chem. Eng. Data 55, 13 (2010)

    Article  CAS  Google Scholar 

  40. N. O. Mchedlov-Petrossyan, Chem. Rev. 113, 5149 (2013)

    Article  CAS  Google Scholar 

  41. I. Z. Kiss, G. Mandi, M.T. Beck, J. Phys. Chem. A 104, 8081 (2000)

    Article  CAS  Google Scholar 

  42. H. Liu, X. Yao, R. Zhang, M. Liu, Z. Hu, B. Fan, J. Phys. Chem. B 109, 20565 (2005)

    Article  CAS  Google Scholar 

  43. F. Gharagheizi, R.F. Alamdari, Fullerenes, Nanotubes, and Carbon Nanostructures 16, 40 (2008)

    Article  CAS  Google Scholar 

  44. T. Petrova, B.F. Rasulev, A.A. Toropov, D. Leszczynska, J. Leszczynski, J. Nanopart. Res. 13, 3235 (2011)

    Article  CAS  Google Scholar 

  45. S. Yousefinejad, F. Honarasa, F. Abbasitabar, Z. Arianezhad, J. Solution Chem. 42, 1620 (2013)

    Article  CAS  Google Scholar 

  46. M. T. Beck, G. Mandi, Fullerenes, Nanotubes, and Carbon Nanostructures 5, 291 (1997)

    CAS  Google Scholar 

  47. R. S. Ruoff, D.S. Tse, R. Malhotra, D.C. Lorents, J. Phys. Chem. 97, 3379 (1993)

    Article  CAS  Google Scholar 

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Authors and Affiliations

  1. Department of Medical and General Chemistry, Bogomolets National Medical University, 01601, Kyiv, Ukraine

    Yaroslava Pushkarova

  2. Materials Chemistry Department, V. N. Karazin Kharkiv National University, 61022, Kharkiv, Ukraine

    Yuriy Kholin

Authors
  1. Yaroslava Pushkarova
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  2. Yuriy Kholin
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Correspondence to Yuriy Kholin.

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Pushkarova, Y., Kholin, Y. A procedure for meaningful unsupervised clustering and its application for solvent classification. cent.eur.j.chem. 12, 594–603 (2014). https://doi.org/10.2478/s11532-014-0514-6

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  • DOI: https://doi.org/10.2478/s11532-014-0514-6

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