Linear fuzzy clustering techniques with missing values and their application to local principal component analysis.
In this paper, we propose two methods for partitioning an incomplete data set with missing values into several linear fuzzy clusters by extracting local principal components. One is an extension of fuzzy c-varieties clustering that can be regarded as the algorithm for the local principal component a...
| Gepubliceerd in: | IEEE Transactions on fuzzy systems 12, 2 (2004). |
|---|---|
| Hoofdauteur: | |
| Formaat: | Artikel |
| Taal: | English |
| Onderwerpen: |