>What does color mean here? What about width of the box?
FWIW, I infer color is solely for visual distinction -- rotating through
orange, red, yellow, pink from left to right. I infer width is proportional
to count of items in each cluster, though apparently not linearly.
I agree that a single plot comparing the algorithms is important since the
purpose of the plot is to compare the algorithms rather than better
understand the data on which they've been run. I haven't thought of a good
way to do that while still having a cluster-by-cluster visual element.
On Fri, Feb 22, 2013 at 12:47 PM, Ted Dunning wrote:
> What does color mean here?
>
> What about width of the box?
>
> When you say median or mean of all cluster distances, do you mean across
> that single run?
>
> I think that this plot is fine as it is except that it needs a legend that
> explains all of these issues. My general rule of thumb is that most
> figures should have what I call a "Kipling caption". See the caption of
> the first image here: http://www.boop.org/jan/justso/butter.htm to see
> what
> I mean by this. Imagine that there is a very mathematically inclined 4
> year old who is looking at your diagram and quizzing you about every part.
> Answer all their questions in the caption and you have a Kipling caption.
>
> For comparing different runs of the clustering or different algorithms, I
> think that a cumulative distribution plot (using plot.ecdf) with all of the
> different algorithms on one plot would be the best comparison tool.
>
> On Fri, Feb 22, 2013 at 8:33 AM, Dan Filimon >wrote:
>
> > As most of the regulars know, I'm working with Ted Dunning on a new
> > clustering framework for Mahout that should land in 0.8.
> >
> > Part of my work is comparing the clustering quality of the new code
> > with the existing Mahout implementation.
> >
> > I compiled a CSV of the quality data [1]. I ran 5 runs of the
> > clustering on the 20 newsgroups data set comparing Mahout KMeans (km),
> > Ball KMeans (bkm), Streaming KMeans (skm) and Streaming KMeans
> > followed by Ball KMeans (bskm).
> >
> > I'm looking at now making some appealing plots for the data. For
> > instance, I think want to make box plots of individual clustering
> > runs. Here's an example [2] of what a clustering looks like for one
> > run of Mahout's standard k-means.
> >
> > There's a box for each cluster, the mean distance is the thick line,
> > the limits are the 1st and 3rd quartiles and the whiskers are the min
> > and max distances.
> > The blue horizontal line is the mean of all average cluster distances.
> > The green horizontal line is the median of all average cluster distances.
> >
> > I intend on making similar plots for the other runs and then
> > aggregating the means of the runs into box plots for the different
> > classes of k-means.
> > The main result being that streaming k-means + ball k-means (as done
> > in the MR) gives a high quality clustering.
> >
> > How do you feel about this plot? Is it too dense? Too colorful? Should
> > I not draw the median any more?
> > What are some other good ways of plotting the quality given the data set?
> >
> > Thanks!
> >
> > [1]
> >
> https://github.com/dfilimon/mahout/blob/skm/examples/src/main/resources/kmeans-comparison-nospace.csv
> > [2]
> >
> http://swarm.cs.pub.ro/~dfilimon/skm-mahout/Mahout%20KMeans%20Run%201.pdf
> >
>