Soft Methods for Data Science

Editors: 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

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.

全目录：


首5章目录：
• Mean Value and Variance of Fuzzy Numbers with Non-continuous Membership Functions
• On the Construction of Radially Symmetric Trivariate Copulas
• Simulation of the Night Shift Solid Waste Collection System of Phuket Municipality
• Updating Context in the Equation: An Experimental Argument with Eye Tracking
• Black-Litterman Model with Multiple Experts’ Linguistic Views

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