Results 41 to 50 of about 867,994 (193)
Assessment of Heart Disease using Fuzzy Classification Techniques
The Scientific World Journal, 2001 In this paper we discuss the classification results of cardiac patients of ischemical cardiopathy, valvular heart disease, and arterial hypertension, based on 19 characteristics (descriptors) including ECHO data, effort testings, and age and weight.
Horia F. Pop, Tudor L. Pop, Costel Sarbu
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A survey of kernel and spectral methods for clustering [PDF]
, 2007 Clustering algorithms are a useful tool to explore data structures and have been employed in many disciplines. The focus of this paper is the partitioning clustering problem with a special interest in two recent approaches: kernel and spectral methods ...
Masulli, F. +11 more
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A Novel Hybrid SBM Clustering Method Based on Fuzzy Time Series
IEEE Access, 2023 With the development of machine learning algorithm and fuzzy theory, the fuzzy clustering algorithm based on time series has received more and more attention. Based on the time series theory and considering the correlation of data attributes, it proposes
Ren-Long Zhang, Xiao-Hong Liu
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 In the process of land cover segmentation from remote sensing image, there are some uncertainties such as “significant difference in class density”, “different objects with same spectrum”, and “same object with ...
Chengmao Wu, Xiaokang Guo
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Performance comparison of fuzzy and non-fuzzy classification methods
Egyptian Informatics Journal, 2016 In data clustering, partition based clustering algorithms are widely used clustering algorithms. Among various partition algorithms, fuzzy algorithms, Fuzzy c-Means (FCM), Gustafson–Kessel (GK) and non-fuzzy algorithm, k-means (KM) are most popular ...
B. Simhachalam, G. Ganesan
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Comparing clustering models in bank customers: Based on Fuzzy relational clustering approach [PDF]
Accounting, 2016 Clustering is absolutely useful information to explore data structures and has been employed in many places. It organizes a set of objects into similar groups called clusters, and the objects within one cluster are both highly similar and dissimilar with
Ayad Hendalianpour +2 more
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Accelerating fuzzy clustering [PDF]
Information Sciences, 2009 This paper extends earlier work [C. Borgelt, R. Kruse, Speeding up fuzzy clustering with neural network techniques, in: Proceedings of the 12th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE'03, St. Louis, MO, USA), IEEE Press, Piscataway, NJ, USA, 2003] on an approach to accelerate fuzzy clustering by transferring methods that were ...
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fcvalid: An R Package for Internal Validation of Probabilistic and Possibilistic Clustering
Sakarya University Journal of Computer and Information Sciences, 2020 In exploratory data analysis and machine learning, partitioning clustering is a frequently used unsupervised learning technique for finding the meaningful patterns in numeric datasets.
Zeynel Cebeci
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Fuzzy Relational Fixed Point Clustering [PDF]
International Journal of Computational Intelligence Systems, 2009 The proposed relational fuzzy clustering method, called FRFP ( fuzzy relational fixed point), is based on determining a fixed point of a function of the desired membership matrix. The ethod is compared to other relational clustering methods.
Roelof K. Brouwer
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A Novel Linguistic Relational Fuzzy C-Means
IEEE AccessIn real-world applications, sometimes there are uncertainties in the data sets whether from the collection process or from the natural languages. Moreover, the data may come in the form of fuzzy relation.
Peerawich Phaknonkul +2 more
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