Comments (1)
Sorry, I was setting a wrong amount of clusters in the constructor.
This is the output now:
Cluster 1 : 10
Cluster 2 : 10
Cluster 3 : 10
Cluster 4 : 10
Cluster 5 : 10
Cluster 6 : 10
Cluster 7 : 10
Cluster 8 : 10
Cluster 9 : 10
Cluster 10 : 10
Total : 100
from same-size-k-means.
Related Issues (10)
- Cluster size are not equal when I use the sparse matrix
- Duplicate code
- Error raised
- Input contains NaN, infinity or a value too large for dtype('float64').
- ImportError: cannot import name '_k_means' from 'sklearn.cluster' HOT 4
- IndexError in sklearn.cluster._k_means._centers_dense
- Is the clustering result stable? HOT 1
- TypeError: _centers_dense() takes exactly 5 positional arguments (4 given)
- Bug ? HOT 4
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from same-size-k-means.