Timeline for Use a clustering as a segmentation
Current License: CC BY-SA 3.0
7 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Dec 6, 2013 at 11:06 | comment | added | Ophelie | Thanks for these answers, but I don't want to change the clusters every week. I add to interpret the results, find clusters names and communicate on the results. What I need to know is when the current clustering has to be changed. | |
| Dec 5, 2013 at 11:14 | comment | added | Has QUIT--Anony-Mousse | Well, you need to make some assumptions how how "latent categories" look like (you surely don't want them to be random; so you cannot be happy without some assumptions). If you have a good reason to assume they are spherical and that Squared Euclidean distance is the proper way of measuring similarity, then k-means is a good choice... If you assume that your latent categoires "look" different, you'll have to use a clustering algorithm that can accomodate this type of restrictions (e.g. density connected clustering such as DBSCAN). | |
| Dec 4, 2013 at 22:50 | comment | added | gung - Reinstate Monica | Thanks for responding so fast. This is an interesting perspective, I wonder if I should start a new thread asking about it. I think of clustering as trying to discover membership in latent categories, not structure. I wonder what the distinction is exactly, what hangs on it, etc. | |
| Dec 4, 2013 at 22:39 | comment | added | Has QUIT--Anony-Mousse | As for the second: I'd suggest to keep summarization separate from clustering. Clustering is supposed to discover structure. If you force the structure to be spherical, that is quite a strong limitation; if you just want to "summarize" your data, look for vector quantization, not structure discovery. | |
| Dec 4, 2013 at 22:36 | comment | added | Has QUIT--Anony-Mousse | Well, there are books on stream clustering, if I'm not mistaken... but I haven't used any of these methods, so I won't be able to give him much details; except to point out that k-means as published by MacQueen in 1967 is already streaming (but most people only know Lloyds k-means algorithm), if he really wants to stick to centroid-based models. | |
| Dec 4, 2013 at 22:30 | comment | added | gung - Reinstate Monica | This seems like a promising start. Can you say more about "stream clustering", & how the OP should be thinking about how to summarize a cluster? | |
| Dec 4, 2013 at 22:27 | history | answered | Has QUIT--Anony-Mousse | CC BY-SA 3.0 |