Abstract
Using fuzzy c-means as the data-mining tool, this study evaluates the effectiveness of sampling methods in producing the knowledge of interest. The effectiveness is shown in terms of the representative-ness of sampling data and both the accuracy and errors of sampled data sets when subjected to the fuzzy clustering algorithm. Two population data in the weld inspection domain were used for the evaluation. Based on the results obtained, a number of observations are made.
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Josien, K., Wang, G., Liao, T.W., Triantaphyllou, E., Liu, M.C. (2001). An Evaluation of Sampling Methods for Data Mining with Fuzzy C-Means. In: Braha, D. (eds) Data Mining for Design and Manufacturing. Massive Computing, vol 3. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-4911-3_15
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DOI: https://doi.org/10.1007/978-1-4757-4911-3_15
Publisher Name: Springer, Boston, MA
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