Reverse Clustering
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Reverse Clustering
This book presents a new perspective on and a new approach to a wide spectrum of situations, related to data analysis, actually, a kind of a new paradigm. Namely, for a given data set and its partition, whose origins may be of any kind, the authors try to reconstruct this partition on the basis of the data set given, using very broadly conceived clustering procedure. The main advantages of this new paradigm concern the substantive aspects of the particular cases considered, mainly in view of the variety of interpretations, which can be assumed in the framework of the paradigm. Due to the novel problem formulation and the flexibility in the interpretations of this problem and its components, the domains, which are encompassed (or at least affected) by the potential use of the paradigm, include cluster analysis, classification, outlier detection, feature selection, and even factor analysis as well as geometry of the data set. The book is useful for all those who look for new, nonconventional approaches to their data analysis problems.
Fuzzy Sets, Rough Sets, Multisets and Clustering
This book is dedicated to Prof. Sadaaki Miyamoto and presents cutting-edge papers in some of the areas in which he contributed. Bringing together contributions by leading researchers in the field, it concretely addresses clustering, multisets, rough sets and fuzzy sets, as well as their applications in areas such as decision-making. The book is divided in four parts, the first of which focuses on clustering and classification. The second part puts the spotlight on multisets, bags, fuzzy bags and other fuzzy extensions, while the third deals with rough sets. Rounding out the coverage, the last part explores fuzzy sets and decision-making.
Decision Making and Decision Support in the Information Era
Author: Valentina Emilia Balas
language: en
Publisher: Springer Nature
Release Date: 2024-08-26
This book is a comprehensive and full-fledged presentation of how modern algorithmic tools and techniques with software implementations can provide an effective and efficient solution of a multitude of problems faced in real life. These problems range from all kinds of data analyses, medical data analyses, image analyses and recognitions, support of medical diagnoses, etc. to new concepts of smart towns and other environments. Emphasis will be on the role of intelligent systems and artificial intelligence and a synergistic collaboration between human beings and computer systems. Modern decision support systems are a main focus point.