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46 | 46 | | Lars Lenssen, Erich Schubert: |
47 | 47 | | Medoid silhouette clustering with automatic cluster number selection |
48 | 48 | | Information Systems (120), 2024, 102290 |
49 | | -| <https://doi.org/10.1016/j.is.2023.102290> |
50 | | -| Preprint: <https://arxiv.org/abs/2309.03751> |
| 49 | +| https://doi.org/10.1016/j.is.2023.102290 |
| 50 | +| Preprint: https://arxiv.org/abs/2309.03751 |
51 | 51 |
|
52 | 52 | | Lars Lenssen, Erich Schubert: |
53 | 53 | | Clustering by Direct Optimization of the Medoid Silhouette |
@@ -525,8 +525,8 @@ def fastmsc(diss, medoids, max_iter=100, init="random", random_state=None): |
525 | 525 | | Lars Lenssen, Erich Schubert: |
526 | 526 | | Medoid silhouette clustering with automatic cluster number selection |
527 | 527 | | Information Systems (120), 2024, 102290 |
528 | | - | <https://doi.org/10.1016/j.is.2023.102290> |
529 | | - | Preprint: <https://arxiv.org/abs/2309.03751> |
| 528 | + | https://doi.org/10.1016/j.is.2023.102290 |
| 529 | + | Preprint: https://arxiv.org/abs/2309.03751 |
530 | 530 |
|
531 | 531 | | Lars Lenssen, Erich Schubert: |
532 | 532 | | Clustering by Direct Optimization of the Medoid Silhouette |
@@ -575,8 +575,8 @@ def fastermsc(diss, medoids, max_iter=100, init="random", random_state=None): |
575 | 575 | | Lars Lenssen, Erich Schubert: |
576 | 576 | | Medoid silhouette clustering with automatic cluster number selection |
577 | 577 | | Information Systems (120), 2024, 102290 |
578 | | - | <https://doi.org/10.1016/j.is.2023.102290> |
579 | | - | Preprint: <https://arxiv.org/abs/2309.03751> |
| 578 | + | https://doi.org/10.1016/j.is.2023.102290 |
| 579 | + | Preprint: https://arxiv.org/abs/2309.03751 |
580 | 580 |
|
581 | 581 | | Lars Lenssen, Erich Schubert: |
582 | 582 | | Clustering by Direct Optimization of the Medoid Silhouette |
@@ -625,8 +625,8 @@ def dynmsc(diss, medoids, max_iter=100, init="random", random_state=None): |
625 | 625 | | Lars Lenssen, Erich Schubert: |
626 | 626 | | Medoid silhouette clustering with automatic cluster number selection |
627 | 627 | | Information Systems (120), 2024, 102290 |
628 | | - | <https://doi.org/10.1016/j.is.2023.102290> |
629 | | - | Preprint: <https://arxiv.org/abs/2309.03751> |
| 628 | + | https://doi.org/10.1016/j.is.2023.102290 |
| 629 | + | Preprint: https://arxiv.org/abs/2309.03751 |
630 | 630 |
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631 | 631 | :param diss: square numpy array of dissimilarities |
632 | 632 | :type diss: ndarray |
@@ -840,8 +840,8 @@ class KMedoids(SKLearnClusterer): |
840 | 840 | | Lars Lenssen, Erich Schubert: |
841 | 841 | | Medoid silhouette clustering with automatic cluster number selection |
842 | 842 | | Information Systems (120), 2024, 102290 |
843 | | - | <https://doi.org/10.1016/j.is.2023.102290> |
844 | | - | Preprint: <https://arxiv.org/abs/2309.03751> |
| 843 | + | https://doi.org/10.1016/j.is.2023.102290 |
| 844 | + | Preprint: https://arxiv.org/abs/2309.03751 |
845 | 845 |
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846 | 846 | | Lars Lenssen, Erich Schubert: |
847 | 847 | | Clustering by Direct Optimization of the Medoid Silhouette |
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