ICAR Research Data Repository for Knowledge Management
Web Based Fuzzy C-means Clustering Software
KrishiKosh
View Archive Info| Field | Value | |
| Title |
Web Based Fuzzy C-means Clustering Software
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| Creator |
Maedeh Zirak Javanmard
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| Contributor |
Alka Arora
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| Subject |
objects, electrophoresis, sets, layering, biological phenomena, extraction, selection, physical control, self help, fruits
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| Description |
T-8480
Fuzzy c-means is a well-known fuzzy clustering algorithm, presented by Dunn [Dunn, 1974] and further developed by J. C. Bezdek [Bezdek, 1981]. Fuzzy clustering method allows objects to belong to several clusters simultaneously with different degrees of membership. Considering the importance of fuzzy clustering, web based software has been developed to implement fuzzy c-means clustering algorithm (wFCM). This paper presents features and functional details of wFCM. wFCM is a freely accessible web based software package for clustering low- and high-dimensional datasets based on fuzzy c-means clustering algorithm. This software is completely menu driven and presents user-friendly GUI which is developed to minimize efforts in using the software. User can upload data to wFCM using three different formats, MS-Excel, CSV and Image file. The key feature of wFCM is that user can visualize the dataset as well as clustering result. Result can be downloadable in Excel and PDF format. This software will be useful for statisticians, researchers, students and teachers for clustering datasets from agricultural research as well as many diverse areas of other sciences. Key words: Web based softw |
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| Date |
2016-11-24T10:14:27Z
2016-11-24T10:14:27Z 2011 |
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| Type |
Thesis
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| Identifier |
http://krishikosh.egranth.ac.in/handle/1/87354
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| Format |
application/pdf
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| Publisher |
IARI, INDIAN AGRICULTURAL STATISTICS RESEARCH INSTITUTE
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