W. Pedrycz
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- Publications
- Influence
An introduction to fuzzy sets : analysis and design
- W. Pedrycz, F. Gomide
- Mathematics
- 1998
Part 1 Fundamentals of fuzzy sets: basic notions and concepts of fuzzy sets - set membership and fuzzy sets, basic definitions of a fuzzy set, types of membership functions, characteristics of a… Expand
A comparative analysis of the efficiency of change metrics and static code attributes for defect prediction
- R. Moser, W. Pedrycz, G. Succi
- Computer Science
- ACM/IEEE 30th International Conference on…
- 15 May 2008
In this paper we present a comparative analysis of the predictive power of two different sets of metrics for defect prediction. We choose one set of product related and one set of process related… Expand
Genetic learning of fuzzy cognitive maps
- W. Stach, L. Kurgan, W. Pedrycz, M. Reformat
- Computer Science, Mathematics
- Fuzzy Sets Syst.
- 1 August 2005
Fuzzy cognitive maps (FCMs) are a very convenient, simple, and powerful tool for simulation and analysis of dynamic systems. They were originally developed in 1980 by Kosko, and since then… Expand
Fuzzy Systems Engineering - Toward Human-Centric Computing
- W. Pedrycz, F. Gomide
- Computer Science
- 13 August 2007
A self-contained treatment of fuzzy systems engineering, offering conceptual fundamentals, design methodologies, development guidelines, and carefully selected illustrative material Forty years have… Expand
- 547
- 36
Fuzzy clustering with partial supervision
- W. Pedrycz, J. Waletzky
- Computer Science, Medicine
- IEEE Trans. Syst. Man Cybern. Part B
- 1 October 1997
Presented here is a problem of fuzzy clustering with partial supervision, i.e., unsupervised learning completed in the presence of some labeled patterns. The classification information is… Expand
Data Mining Methods for Knowledge Discovery
- K. Cios, W. Pedrycz, R. Swiniarski
- Computer Science
- IEEE Trans. Neural Networks
- 31 August 1998
Foreword. Preface. 1. Data Mining and Knowledge Discovery. 2. Rough Sets. 3. Fuzzy Sets. 4. Bayesian Methods. 5. Evolutionary Computing. 6. Machine Learning. 7. Neural Networks. 8. Clustering. 9.… Expand
Conditional fuzzy clustering in the design of radial basis function neural networks
- W. Pedrycz
- Medicine, Computer Science
- IEEE Trans. Neural Networks
- 1 July 1998
This paper is concerned with the use of radial basis function (RBF) neural networks aimed at an approximation of nonlinear mappings from R(n) to R. The study is devoted to the design of these… Expand
Kernel-based fuzzy clustering and fuzzy clustering: A comparative experimental study
- Daniel Graves, W. Pedrycz
- Mathematics, Computer Science
- Fuzzy Sets Syst.
- 1 February 2010
In this study, we present a comprehensive comparative analysis of kernel-based fuzzy clustering and fuzzy clustering. Kernel based clustering has emerged as an interesting and quite visible… Expand
Rough–Fuzzy Collaborative Clustering
- S. Mitra, H. Banka, W. Pedrycz
- Computer Science, Medicine
- IEEE Transactions on Systems, Man, and…
- 1 August 2006
In this study, we introduce a novel clustering architecture, in which several subsets of patterns can be processed together with an objective of finding a common structure. The structure revealed at… Expand
Shadowed sets: representing and processing fuzzy sets
- W. Pedrycz
- Medicine, Computer Science
- IEEE Trans. Syst. Man Cybern. Part B
- 1 February 1998
This study introduces a new concept of shadowed sets that can be regarded as a certain operational framework simplifying processing carried out with the aid of fuzzy sets and enhancing interpretation… Expand