.png){kind=icon}
Return
Semi-supervised fuzzy clustering: A kernel-based approach
.png){kind=icon}
PRE
AI
DOI：10.1016/j.knosys.2009.06.009.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Semi-supervised clustering algorithms aim to improve the clustering accuracy under the supervisions of a limited amount of labeled data. Since kernel-based approaches, such as kernel-based fuzzy c-means algorithm (KFCM), have been successfully used in classification and clustering problems, in this paper, we propose a novel semi-supervised clustering approach using the kernel-based method based on KFCM and denote it the semi-supervised kernel fuzzy c-mean algorithm (SSKFCM). The objective function of SSKFCM is defined by adding classification errors of both the labeled and the unlabeled data, and its global optimum has been obtained through repeatedly updating the fuzzy memberships and the optimized kernel parameter. The objective function may have more than one local optimum, so we employ a function transformation technique to reformulate the objective function after a local minimum has been obtained, and select the best optimum as the solution to the objective function. Experimental results on both the artificial and several real data sets show SSKFCM performs better than its conventional counterparts and it achieves the best accurate clustering results when the parameter is optimized. (C) 2009 Elsevier B.V. All rights reserved.
Keywords:
Semi-supervised clustering
Kernel parameter
Optimization
Deflection
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
K
IF:
7.6
Papers:
1.3W
Citations:
4.5W
Organization
Cited Papers
ShareSaveShareSaveEvaluation of the performance of clustering algorithms in kernel-induced feature space.png)
PATTERN RECOGNITION
PATTERN RECOGNITIONIF7.6
PREAI
ShareSaveCan primary care research be conducted more efficiently using routinely reported practice-level data: a cluster randomised controlled trial conducted in England?BMJ Open
OAAI
BMJ OpenIF0
OAAIShareSave
View more