© 2017

Soft Methods for Data Science

  • Maria Brigida Ferraro
  • Paolo Giordani
  • Barbara Vantaggi
  • Marek Gagolewski
  • María Ángeles Gil
  • Przemysław Grzegorzewski
  • Olgierd Hryniewicz


  • Latest research on Data Analysis and Soft Computing

  • Results of the 8th International Conference on Soft Methods in Probability and Statistics (SMPS'2016) held in Rome (Italy) by September 12-14, 2016

  • Gives a comprehensive overview of current research into the fusion of soft computing methods with probability and statistics

Conference proceedings SMPS 2016

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 456)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. José De Jesús Arias García, Hans De Meyer, Bernard De Baets
    Pages 9-15
  3. Jean Baratgin, Brian Ocak, Hamid Bessaa, Jean-Louis Stilgenbauer
    Pages 25-33
  4. Marcin Bartkowiak, Aleksandra Rutkowska
    Pages 35-43
  5. Salem Benferhat, Khaoula Boutouhami, Faiza Khellaf, Farid Nouioua
    Pages 45-52
  6. Patrizia Berti, Luca Pratelli, Pietro Rigo
    Pages 53-60
  7. Angela Blanco-Fernández, Ana B. Ramos-Guajardo
    Pages 61-68
  8. Christian Borgelt, Rudolf Kruse
    Pages 69-77
  9. Dario Briscolini, Brunero Liseo, Andrea Tancredi
    Pages 79-86
  10. Andrey G. Bronevich, Igor N. Rozenberg
    Pages 87-94
  11. Gianluca Cassese
    Pages 103-111
  12. Marco E. G. V. Cattaneo
    Pages 113-120
  13. Bekir Cetintav, Selma Gurler, Neslihan Demirel, Gozde Ulutagay
    Pages 121-126
  14. Giulianella Coletti, Davide Petturiti, Barbara Vantaggi
    Pages 127-134
  15. Ana Colubi, Gil Gonzalez-Rodriguez
    Pages 135-140
  16. Marcello D’Orazio, Marco Di Zio, Mauro Scanu
    Pages 149-156

About these proceedings


This proceedings volume is a collection of peer reviewed papers presented at the 8th International Conference on Soft Methods in Probability and Statistics (SMPS 2016) held in Rome (Italy).

The book is dedicated to Data science which aims at developing automated methods to analyze massive amounts of data and to extract knowledge from them. It shows how Data science employs various programming techniques and methods of data wrangling, data visualization, machine learning, probability and statistics. The soft methods proposed in this volume represent a collection of tools in these fields that can also be useful for data science.


Computational Intelligence Intelligent Data Analysis Soft Computing SMPS 2016 Statistics

Editors and affiliations

  • Maria Brigida Ferraro
    • 1
  • Paolo Giordani
    • 2
  • Barbara Vantaggi
    • 3
  • Marek Gagolewski
    • 4
  • María Ángeles Gil
    • 5
  • Przemysław Grzegorzewski
    • 6
  • Olgierd Hryniewicz
    • 7
  1. 1.Department of Statistical SciencesSapienza University of RomeRomeItaly
  2. 2.Department of Statistical SciencesSapienza University of RomeRomaItaly
  3. 3.Dept of Basic & Applied Sciences EnggSapienza University of RomeRomeItaly
  4. 4.Dept of Stoc Metds,Polish Academy of SciSystems Research InstituteWarsawPoland
  5. 5.Dept of Statis&OR and MDUniv de OviedoOviedoSpain
  6. 6.Dept of Stoc Metds,Polish Aca of ScienceSystems Res InstWarsawPoland
  7. 7.Sys Res Inti, Dept of Stoch MethodsPolish Acadmy Sci in WarsawWarsawPoland

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