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 <dangeorge.filimon@gmail.com>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 kmeans.
>
> 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 kmeans.
> The main result being that streaming kmeans + ball kmeans (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/kmeanscomparisonnospace.csv
> [2]
> http://swarm.cs.pub.ro/~dfilimon/skmmahout/Mahout%20KMeans%20Run%201.pdf
>
