Towards Advanced Data Analysis by Combining Soft Computing and Statistics edited by Christian Borgelt, María Ángeles Gil, João M.C. Sousa, Michel Verleysen.

Soft computing, as an engineering science, and statistics, as a classical branch of mathematics, emphasize different aspects of data analysis. Soft computing focuses on obtaining working solutions quickly, accepting approximations and unconventional approaches. Its strength lies in its flexibility t...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Borgelt, Christian (Editor), Gil, María Ángeles (Editor), Sousa, João M.C (Editor), Verleysen, Michel (Editor)
Format: eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Edition:1st ed. 2013.
Series:Studies in Fuzziness and Soft Computing, 285
Springer eBook Collection.
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Online Access:Click to view e-book
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Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • From the Contents: Arithmetic and Distance-Based Approach to the Statistical Analysis of Imprecisely Valued Data
  • Linear Regression Analysis for Interval-valued Data Based on Set Arithmetic: A Bootstrap Confidence Intervals for the Parameters of a Linear Regression Model with Fuzzy Random Variables
  • On the Estimation of the Regression Model M for Interval Data
  • Hybrid Least-Squares Regression Modelling Using Confidence
  • Testing the Variability of Interval Data: An Application to Tidal Fluctuation.-Comparing the Medians of a Random Interval Defined by Means of Two Different L1 Metrics.-Comparing the Representativeness of the 1-norm Median for Likert and Free-response Fuzzy Scales.-Fuzzy Probability Distributions in Reliability Analysis, Fuzzy HPD-regions, and Fuzzy Predictive Distributions.