Towards Advanced Data Analysis by Combining Soft Computing and Statistics

• Corporate Author: SpringerLink (Online service)
• Other Authors: Borgelt, Christian. (Editor), Gil, Mara̕ ℓngeles. (Editor), Sousa, Joô M.C. (Editor), Verleysen, Michel. (Editor)
• Format: Electronic
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
• Series: Studies in Fuzziness and Soft Computing, 285
• Subjects: Engineering.; Computer science.; Data mining.; Computer simulation.; Computational Intelligence.; Probability and Statistics in Computer Science.; Data Mining and Knowledge Discovery.; Simulation and Modeling.
• Online Access: https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-30278-7

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...

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.