Talk:Consensus clustering: Difference between revisions

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Needs expansion

Please, more reference and expand description of the alghorithms. 00:55, 7 October 2010 178.73.63.95 (talk)

Yes, effectively no information here. Melcombe (talk) 16:46, 13 December 2010 (UTC)[reply]

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Problems with the PAC score

I noticed the author of the PAC score paper has inserted a section on their method with graphics on this page. I think this is fine, as it is an important addition to the Monti consensus clustering method (which I have now added mathematical detail on), although I did reduce the detail on this one paper a bit, because I thought it was over glorified. We have found in practice the PAC score works poorly because it overestimates K all the time, in the scientific reports paper the method was not tested on real data, instead just simulations were used. We have fixed this method by adding a Monte Carlo simulation to the Monti consensus clustering algorithm (M3C). I added a brief few sentences to explain this method. However, there is a wikipedia user 'HelpUsStopSpam' who thought this section should be deleted because I am the primary author of the paper. I really do think a new comment should be added at somepoint to explain the inherant bias of the Monti consensus clustering algorithm and the PAC score. A sentence or two is all that is required. Basically, as K increases so does the stability of the consensus matrix on random data, this is a major problem we have noticed again and again on cancer and other datasets. Thank you.

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 ==Needs expansion==
 Please, more reference and expand description of the alghorithms. 00:55, 7 October 2010 178.73.63.95 (talk)
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 == Problems with the PAC score ==
-I noticed the author of the PAC score paper has inserted a large section on their method with graphics on this page. I think this is fine, as it is an important addition to the Monti consensus clustering method (which I have now added mathematical detail on). However, we have found in practice the PAC score works poorly because it overestimates K all the time, in the scientific reports paper the method was not tested on real data, instead just simulations were used. We have fixed this method by adding a Monte Carlo simulation to the Monti consensus clustering algorithm (M3C). I have added a small paragraph to mention this method. However, there is a wikipedia user 'HelpUsStopSpam' who thought this paragraph should be deleted. Please if you see it being removed again, it is important to keep this paragraph and this deletion should be undone in my opinion, having actually worked in this field for some time.
+I noticed the author of the PAC score paper has inserted a section on their method with graphics on this page. I think this is fine, as it is an important addition to the Monti consensus clustering method (which I have now added mathematical detail on), although I did reduce the detail on this one paper a bit, because I thought it was over glorified. We have found in practice the PAC score works poorly because it overestimates K all the time, in the scientific reports paper the method was not tested on real data, instead just simulations were used. We have fixed this method by adding a Monte Carlo simulation to the Monti consensus clustering algorithm (M3C). I added a brief few sentences to explain this method. However, there is a wikipedia user 'HelpUsStopSpam' who thought this section should be deleted because I am the primary author of the paper. I really do think a new comment should be added at somepoint to explain the inherant bias of the Monti consensus clustering algorithm and the PAC score. A sentence or two is all that is required. Basically, as K increases so does the stability of the consensus matrix on random data, this is a major problem we have noticed again and again on cancer and other datasets. Thank you.