Hi,

Thanks for reply. The thing is that z matrix (dataset1MC$z) gives only
1.00,  if point is classified to particular cluster:

        [,1]         [,2]
NA12043 1.000000e+00 2.608455e-15
NA12249 1.000000e+00 7.784309e-15
NA12264 1.000000e+00 1.664289e-25
NA12234 3.151495e-19 1.000000e+00
NA12236 1.000000e+00 4.399892e-21

It means that samples NA12043, NA12249, NA12264, NA12236 are in the same
group nr 1, and NA12234 is in group nr 2, but there's no information how
strong they belong to their groups.

> high.conf
NA12043 NA12249 NA12264 NA12707 NA12716 NA12717 NA12751 NA12762 NA12864
NA12873 NA07034 NA07048 NA07055 NA07345 NA07348 NA07357 NA10830 NA10835
NA12154 NA12234 NA12236 NA12763 NA12801 NA12812 NA12813 NA12878 NA10851
NA10854 NA10857
   TRUE    TRUE    TRUE    TRUE    TRUE    TRUE    TRUE    TRUE    TRUE
 TRUE    TRUE    TRUE    TRUE    TRUE    TRUE    TRUE    TRUE    TRUE
 TRUE    TRUE    TRUE    TRUE    TRUE    TRUE    TRUE    TRUE    TRUE
 TRUE    TRUE
NA10859 NA10861 NA10863 NA11839 NA11840 NA11881 NA11882 NA11994 NA12044
NA12056 NA12057 NA12891 NA12892
   TRUE    TRUE    TRUE    TRUE    TRUE    TRUE    TRUE    TRUE    TRUE
 TRUE    TRUE    TRUE    TRUE

true, but no:)

THX

Bas.

2012/1/27 Steve Lianoglou <mailinglist.honeypot@gmail.com>

> Hi,
>
> On Fri, Jan 27, 2012 at 8:28 AM, Barbara Uszczynska
> <uszczynska@gmail.com> wrote:
> > Dear Conductors,
> >
> > I was wondering if there's any simple way of calculating the probability
> of
> > a point membership to a certain cluster. I'm using EM algorithm from
> mclust
> > package to analyse my data. As an output of classification I obtain data
> > grouped into clusters and I can have a matrix whose the element in
> position
> > [I,k] presents the conditional probability of the ith point belongs to
> the
> > kth cluster. However, I would like to get something more precise, as a
> > probability of belongness for each point only from given cluster. For
> > example, If I get my data divided into 3 groups by EM algorithm, I would
> > like to know how strong each point from cluster 1 belongs to this
> cluster, how
> > strong each point from cluster 2 belongs to this cluster and how strong
> > each point from cluster 3 belongs to this cluster.
>
> I probably shouldn't be answering these types of emails until I (at
> least) finish my first coffee, but I'm a bit lost. The "thing" that
> you are describing that you want is actually the `z` matrix you are
> returned from Mclust (which you also describe above).
>
> It's not clear (to me, anyways) how the second scenario you describe
> is different than what z is -- hopefully someone else will be able to
> ring in w/ more clarity.
>
> > I was thinking about the
> > creating some kind of parameter, which will allow me to see points with
> > highest/strongest membership...like show me all points, which belong to
> > their clusters with probability higher than 0.8.
> >
> > library(mclust)
> >
> > dataset1MC<-Mclust(dataset1)
> > plot(dataset1MC, dataset1)
> >
> > dataset1MC$z
>
> In your code above, you can just query `$z` for that, no? Wouldn't
> this do what you want:
>
> R> high.conf <- apply(dataset1MC$z, 1, function(row) any(row > 0.8))
>
> Yes?
> No?
>
> HTH,
> -steve
>
> --
> Steve Lianoglou
> Graduate Student: Computational Systems Biology
>  | Memorial Sloan-Kettering Cancer Center
>  | Weill Medical College of Cornell University
> Contact Info: http://cbio.mskcc.org/~lianos/contact
>

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