Good job Pierre !
I was looking exactly to the same document recently and thought that I
could try to reproduce some examples from chapter 3.
Maybe we can join our effort and reproduce the examples as a Pillar chapter
somewhere ?
Regards,
On Sat, Jun 27, 2015 at 12:16 AM, Pierre CHANSON <chans.pierre(a)gmail.com>
wrote:
Hola todos,
These days I am working on compete with R. I am taking the datasets and
examples from
http://cran.r-project.org/doc/contrib/Zhao_R_and_data_mining.pdf and make
it with Roassal even better ! Or almost... ;)
First chapter first pages, the histograms... In Roassal they were not
working so well.
So lately I restructured the RTDistribution package. This, by default make
a classical frequency distribution, with an optimized number of classes.
The method #strategyBlock: allows to change the strategy for the
distribution.
I also worked on the RTHistogramSet and method #histogram of
SequenceableCollection to improve a bit the looking. There is still here
some work to do but at least the histogram works well and looks fine.
We worked with Alejandro on the algorithm of frequency distribution to
make it efficient compared to the classic one (Only one iteration on datas
during the algo itself).
Here are some examples, don't hesitate to try a bit and give me feedbacks
if any bugs, so I can move on the next graphs ;)
#(5 3 8 6 5 4 2 9 1 2) histogram.
#(1 2 3) histogram.
#(555 1 1 2) histogram.
((1 to: 1000) collect: [:i | i atRandom ]) histogram.
Also, I found this page and thought it was really nice animations !!
http://bost.ocks.org/mike/algorithms/
cheers,
Pierre
_______________________________________________
Moose-dev mailing list
Moose-dev(a)iam.unibe.ch
https://www.iam.unibe.ch/mailman/listinfo/moose-dev
--
Serge Stinckwich
UCBN & UMI UMMISCO 209 (IRD/UPMC)
Every DSL ends up being Smalltalk
http://www.doesnotunderstand.org/