other:inspect3d:tutorials:run_k-means
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| other:inspect3d:tutorials:run_k-means [2025/01/16 20:45] – wikisysop | other:inspect3d:tutorials:run_k-means [2025/01/16 20:47] (current) – wikisysop | ||
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| 11. Close the {{: | 11. Close the {{: | ||
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| ==== Interpreting K-Means Results ==== | ==== Interpreting K-Means Results ==== | ||
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| Looking at the workspace tab we can select different points and the group and file will be displayed. This allows us to view which data points in a cluster belong to what group. We can clearly see the data points split into to clusters, light blue and dark blue, with somewhat of a separation. Light blue tends to be in the top right corner and dark blue tends to be in the bottom left. | Looking at the workspace tab we can select different points and the group and file will be displayed. This allows us to view which data points in a cluster belong to what group. We can clearly see the data points split into to clusters, light blue and dark blue, with somewhat of a separation. Light blue tends to be in the top right corner and dark blue tends to be in the bottom left. | ||
| - | {{: | + | {{:k-MeansResults3.png}} |
| A K-means test finds the similarity between data points and groups them together into clusters. If you had two groups that were vastly different, the clusters would not have mixed groups. If the data points between groups have similarities the clusters may have data points from different groups. | A K-means test finds the similarity between data points and groups them together into clusters. If you had two groups that were vastly different, the clusters would not have mixed groups. If the data points between groups have similarities the clusters may have data points from different groups. | ||
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| If we look at the results from this K-Means we can see that the clusters are not a perfect representation of each group, signifying that there is some overlap and similarities between groups. The graph on the left shows the groups split up with the osteoarthritis group in purple and the normal group in blue. The graph on the right shows the two clusters. If we look at the light blue cluster it seems to be mainly the osteoarthritis group, and if we look at the dark blue cluster it seems to be mainly the normal group. The points circled in red show some osteoarthritis datapoints in the second cluster, again indicating some overlap. | If we look at the results from this K-Means we can see that the clusters are not a perfect representation of each group, signifying that there is some overlap and similarities between groups. The graph on the left shows the groups split up with the osteoarthritis group in purple and the normal group in blue. The graph on the right shows the two clusters. If we look at the light blue cluster it seems to be mainly the osteoarthritis group, and if we look at the dark blue cluster it seems to be mainly the normal group. The points circled in red show some osteoarthritis datapoints in the second cluster, again indicating some overlap. | ||
| - | {{: | + | {{:k-MeansResults2.png}} |
other/inspect3d/tutorials/run_k-means.1737060322.txt.gz · Last modified: 2025/01/16 20:45 by wikisysop