Optimizing MSE for Clustering with Balanced Size Constraints
Clustering is to group data so that the observations in the same group are more similar to each other than to those in other groups. k-means is a popular clustering algorithm in data mining. Its objective is to optimize the mean squared error (MSE). The traditional k-means algorithm is not suitable...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-03-01
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| Series: | Symmetry |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2073-8994/11/3/338 |