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<pre>
Michael Emmerich
Vasyl Lytvyn
Iryna Yevseyeva
Vitor Basto-Fernandes
Dmytro Dosyn
Victoriа Vysotska
(Eds.)




     Modern Machine
   Learning Technologies
     and Data Science
        Workshop
    Workshop Proceedings of the 8th International
 Conference on “Mathematics. Information Technolo-
  gies. Education”, MoMLeT&DS Workshop 2019


  Shatsk, Ukraine
  June, 2019
Emmerich, M., Lytvyn, V., Yevseyeva, I., Basto-Fernandes, V., Dosyn, D., Vysotska,
V. (Eds.): Modern Machine Learning Technologies and Data Science Workshop.
Proc. 1st International Workshop MoMLeT&DS 2019. Shatsk, Ukraine, June 2-4,
2019, CEUR-WS.org, online




This volume represents the proceedings of the Workshop of the 8th International Con-
ference on “Mathematics. Information Technologies. Education”, with Posters and
Demonstrations track, of the 1st International Workshop of Modern Machine Learning
Technologies and Data Science, held in Shatsk, Ukraine, in June 2019. It comprises
28 contributed papers that were carefully peer-reviewed and selected from 59 sub-
missions. The volume opens with the abstracts of the keynote talks. The rest of the
collection is organized in two parts. Parts I contain the contributions to the Main
MoMLeT&DS Workshop tracks, structured in two topical sections: (I) Modern Ma-
chine Learning Technologies; (II) Data Science.




        Copyright © 2019 for the individual papers by the papers’ authors.
        Copying permitted only for private and academic purposes. This
        volume is published and copyrighted by its editors.
                                    Preface
It is our pleasure to present you the proceedings of the MoMLeT&DS Workhop of
the 8th International Conference on “Mathematics. Information Technologies. Educa-
tion”, the first edition of the Modern Machine Learning Technologies and Data Sci-
ence Workshop, held in Shatsk (Ukraine) on June 2-4, 2019.

The main purpose of the MoMLeT&DS Workhop is to provide a forum for research-
ers to discuss models for machine learning, multicriteria decision analysis and multi-
objective optimization, and their real-life applications. In MoMLeT&DS 2019, is
encourage the submission of papers on machine learning, decision making, multi-
objective optimization and multicriteria decision analysis areas. Novel applications of
these methods to real world problems are welcome.

The conference is soliciting literature review, survey and research papers comments
including, whilst not limited to, the following areas of interest:
      Regression analysis;
      Deep learning;
      Gradient Boosted Trees;
      Support Vector Machines;
      Bayesian networks;
      Unsupervised learning for clustering;
      MCDM Theory;
      Multiobjective Optimization;
      Group Decision Making;
      Multiattribute Utility or Value Theory;
      Behavioral Issues in Decision Making;
      Preference Modelling;
      Applications of MCDM and Optimization.

The language of MoMLeT&DS Conference is English.

The conference took the form of oral presentation by invited keynote speakers plus
presentations of peer-reviewed individual papers. There was also an exhibition area
for poster and demo sessions. A Student section of the conference for students and
PhD students run in parallel to the main conference.

This year Organizing Committee received 59 submissions, out of which 28 were ac-
cepted for presentation as a regular papers. The papers are submitted to the following
tracks: Regression analysis (5 papers); Deep learning (6 papers); Gradient Boosted
Trees (3 papers); Support Vector Machines (4 papers); Bayesian networks (7 papers);
Unsupervised learning for clustering (5 papers); MCDM Theory (2 papers); Multi-
objective Optimization (2 papers); Group Decision Making (2 papers); Multiattribute
Utility or Value Theory (3 papers); Behavioral Issues in Decision Making (6 papers);
Preference Modelling (5 papers); Applications of MCDM and Optimization
(2 papers).
These papers and extended abstracts were published in this Volume of MoMLeT&DS
Workshop 2019 proceedings.

The conference would not have been possible without the support of many people.
First of all, we would like to thank all the authors who submitted papers to
MoMLeT&DS 2019 and thus demonstrated their interest in the research problems
within our scope. We are very grateful to the members of our Program Committee for
providing timely and thorough reviews and, also, for being cooperative in doing addi-
tional review work. We would like to thank the Organizing Committee of the confer-
ence whose devotion and efficiency made this instance of MoMLeT&DS a very in-
teresting and effective scientific forum.

June, 2019                                          Michael Emmerich
                                                    Vasyl Lytvyn
                                                    Iryna Yevseyeva
                                                    Vitor Basto-Fernandes
                                                    Dmytro Dosyn
                                                    Victoriа Vysotska

</pre>