| commit | 4d14b55ee7237f7ad109f4fae5c3e515a0120a41 | [log] [tgz] |
|---|---|---|
| author | Jingning Han <jingning@google.com> | Fri Apr 12 22:59:51 2019 |
| committer | Jingning Han <jingning@google.com> | Fri Apr 12 22:59:51 2019 |
| tree | 5b80233f42ee0d0a5cca05db8c124bcf16dfeb26 | |
| parent | b758ba795a04d551caa3c1af2806cdf0c075803a [diff] |
Use uniform sampling as initial centers for k-means The Wiener variance output has been sorted prior to the clustering, which allows to directly use the uniform sampling as the initial center points. It avoids empty cluster situations when the samples are heavily distributed at two far ends and leave the middle empty. Change-Id: I159fbfa6bbb4aafd19411fd005666d144cca30fc