A Heuristic Approach to Possibilistic Clustering. Algorithms and Applications

A Heuristic Approach to Possibilistic Cl

📁 A Heuristic Approach to Possibilistic Clustering: Algorithms and Applications

✍ Dmitri A. Viattchenin (auth.) 📂 Library 📅 2013 🏛 Springer-Verlag Berlin Heidelberg 🌐 English

The present book outlines a new approach to possibilistic clustering in which the sought clustering structure of the set of objects is based directly on the formal definition of fuzzy cluster and the possibilistic memberships are determined directly from the values of the pairwise similarity o

Bayesian Heuristic Approach to Discrete

📁 Bayesian Heuristic Approach to Discrete and Global Optimization: Algorithms, Visualization, Software, and Applications

✍ Jonas Mockus, William Eddy, Audris Mockus, Linas Mockus, Gintaras Reklaitis (aut 📂 Library 📅 1997 🏛 Springer US 🌐 English

Bayesian decision theory is known to provide an effective framework for the practical solution of discrete and nonconvex optimization problems. This book is the first to demonstrate that this framework is also well suited for the exploitation of heuristic methods in the solution of such problems,

Data Clustering: Algorithms and Applicat

📁 Data Clustering: Algorithms and Applications

✍ Charu C. Aggarwal, Chandan K. Reddy 📂 Library 📅 2014 🏛 CRC Press 🌐 English

Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, fr

Data Clustering: Algorithms and Applicat

📁 Data Clustering: Algorithms and Applications

✍ Aggarwal, Charu C.(ed.); Reddy, Chandan K (ed.) 📂 Library 📅 2014 🏛 Chapman and Hall/CRC 🌐 English

Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, fr

Data Clustering: Algorithms and Applicat

📁 Data Clustering: Algorithms and Applications

✍ Charu C. Aggarwal, Chandan K. Reddy 📂 Library 📅 2013 🏛 Chapman and Hall/CRC 🌐 English

Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire ar

Parallel Algorithms and Cluster Computin

📁 Parallel Algorithms and Cluster Computing: Implementations, Algorithms and Applications

✍ Karl Heinz Hoffmann, Arnd Meyer 📂 Library 📅 2006 🏛 Springer 🌐 English

This book presents major advances in high performance computing as well as major advances due to high performance computing. It contains a collection of papers in which results achieved in the collaboration of scientists from computer science, mathematics, physics, and mechanical engineering are pre