Timeline for Regression with variable containing multiple entries per observation - clustering right approach?
Current License: CC BY-SA 3.0
13 events
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Apr 9, 2016 at 19:23 | answer | added | Has QUIT--Anony-Mousse | timeline score: 0 | |
Apr 9, 2016 at 19:16 | history | edited | Has QUIT--Anony-Mousse | CC BY-SA 3.0 |
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Apr 9, 2016 at 15:39 | history | edited | JNWHH | CC BY-SA 3.0 |
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Apr 8, 2016 at 10:39 | answer | added | user78229 | timeline score: 1 | |
Apr 8, 2016 at 10:05 | history | edited | JNWHH | CC BY-SA 3.0 |
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Apr 8, 2016 at 9:59 | comment | added | JNWHH | Thanks for challenging my question - I reframed my question and included my overall goal since maybe clustering overall is not the right approach | |
Apr 8, 2016 at 9:59 | history | edited | JNWHH | CC BY-SA 3.0 |
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Apr 8, 2016 at 7:58 | comment | added | ttnphns | Check additionally stats.stackexchange.com/q/44640/3277, stats.stackexchange.com/q/89535/3277, stats.stackexchange.com/q/105838/3277. If these didn't help you then please say it in your question - why; what makes your problem different or what dissatisfied you in the recipes already given. | |
Apr 8, 2016 at 7:50 | comment | added | JNWHH | I did (you can also see "related" questions on the right). However those questions (3-4) where either in a different context, differed on one key dimension (e.g., my matrix is extremely sparse) or didn't provide any helpful solution. | |
Apr 8, 2016 at 7:35 | comment | added | ttnphns |
This sort of question was asked several times here, I expect. Did you try first a search of clustering binary sparse ?
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Apr 8, 2016 at 7:31 | history | edited | ttnphns | CC BY-SA 3.0 |
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Apr 8, 2016 at 6:06 | review | First posts | |||
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Apr 8, 2016 at 6:01 | history | asked | JNWHH | CC BY-SA 3.0 |