Timeline for Performing a Self-Organizing Map on multiple distance matrices in R with a better visualization
Current License: CC BY-SA 3.0
7 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jul 22, 2013 at 15:36 | answer | added | Gavin Simpson | timeline score: 1 | |
| Jul 22, 2013 at 7:50 | comment | added | POD | @PeterEllis I only clustered one of the matrices. I have made a random case and feed it to the SOM, but the results are stupid!! they seem like wave lines to me. Can I get a heatmap or something that reperesent the data better? | |
| Jul 22, 2013 at 6:54 | comment | added | Peter Ellis | ok, but in your example graphic you have just one distance matrix, right? It seems to me a first step is to get that visualisation right (or at a minimum, understood and interpretable) and then deal with the more complex situation. If you could fix and understand this graphic, the solution might be as simple as faceting it in the style of ggplot or lattice. Alternatively if this graphic is on completely the wrong basis (your data doesn't seem to resemble that in the example in the help file) you may need a new start. | |
| Jul 22, 2013 at 6:44 | comment | added | POD | @PeterEllis I have to cluster all of these elements together. I believe that combining all of these matrices together and performing a clustering analysis would be more acceptable than clustering each of matrices and then combining them. Although I am open to suggestions. | |
| Jul 22, 2013 at 6:31 | comment | added | Peter Ellis | You have a number of distance matrices, but is your question how represent just one of these at a time, or all of them together? In other words, is this a question about visualising a single distance matrix, which you can then apply to each one at a time, or of multiple matrices? | |
| Jul 22, 2013 at 5:04 | history | edited | POD | CC BY-SA 3.0 |
edited title
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| Jul 22, 2013 at 4:54 | history | asked | POD | CC BY-SA 3.0 |