Abstract This publication deals with the applicational aspects and possibilities of the Complete Gradient Clustering Algorithm—the classic procedure of Fukunaga and Hostetler, prepared to a ready-to-use state, by providing a full set of procedures for defining all functions and the values of parameters. Moreover, it describes how a possible change in those values influences the number of clusters and the proportion between their numbers in dense and sparse areas of data elements. The possible uses of these properties were illustrated in practical tasks from bioinformatics (the categorization of grains for seed production), management (the design of a marketing support strategy for a mobile phone operator) and engineering (the synthesis of a...
Kernel approaches call improve the performance of conventional Clustering or classification algorith...
Algorithms for automatic selection of seed points for clustering are described using the terms 'inde...
Fuzzy clustering using MDSCAL / Jürgen Hansohm ; Martin Schader. - In: Symposium on Operations Resea...
The aim of this paper is to present a Complete Gradient ClusteringAlgorithm, its applicational aspec...
The aim of this paper is to provide a gradient clustering algorithm in its complete form, suitable f...
Data clustering constitutes at present a commonly used technique for extracting fuzzy system rules f...
Deriving parameters and structure of fuzzy model for a dynamical system by means of a clustering pro...
For real-world clustering tasks, the input data is typically not easily separable due to the highly ...
Abstract:- Fuzzy clustering is a data analysis technique that, when applied to a set of heterogeneou...
In this paper, site-specific management zones (MZs) were delineated in three fields belonging to a f...
The aim of this paper is to provide a gradient clustering algorithm in its complete form, suitable f...
textabstractFuzzy clustering is a widely applied method for obtaining fuzzy models from data. It has...
In fuzzy control, there is a large amount of parameters involved in the system design. Due to their ...
In data analysis and data mining technique fields, one of the most widely used methods is clustering...
Fuzzy clustering is a widely applied method for obtaining fuzzy models from data. It has been applie...
Kernel approaches call improve the performance of conventional Clustering or classification algorith...
Algorithms for automatic selection of seed points for clustering are described using the terms 'inde...
Fuzzy clustering using MDSCAL / Jürgen Hansohm ; Martin Schader. - In: Symposium on Operations Resea...
The aim of this paper is to present a Complete Gradient ClusteringAlgorithm, its applicational aspec...
The aim of this paper is to provide a gradient clustering algorithm in its complete form, suitable f...
Data clustering constitutes at present a commonly used technique for extracting fuzzy system rules f...
Deriving parameters and structure of fuzzy model for a dynamical system by means of a clustering pro...
For real-world clustering tasks, the input data is typically not easily separable due to the highly ...
Abstract:- Fuzzy clustering is a data analysis technique that, when applied to a set of heterogeneou...
In this paper, site-specific management zones (MZs) were delineated in three fields belonging to a f...
The aim of this paper is to provide a gradient clustering algorithm in its complete form, suitable f...
textabstractFuzzy clustering is a widely applied method for obtaining fuzzy models from data. It has...
In fuzzy control, there is a large amount of parameters involved in the system design. Due to their ...
In data analysis and data mining technique fields, one of the most widely used methods is clustering...
Fuzzy clustering is a widely applied method for obtaining fuzzy models from data. It has been applie...
Kernel approaches call improve the performance of conventional Clustering or classification algorith...
Algorithms for automatic selection of seed points for clustering are described using the terms 'inde...
Fuzzy clustering using MDSCAL / Jürgen Hansohm ; Martin Schader. - In: Symposium on Operations Resea...