From: Benjamin Auder Date: Fri, 22 Jul 2016 14:44:30 +0000 (+0200) Subject: readme.md X-Git-Url: https://git.auder.net/doc/html/vendor/current/git-favicon.png?a=commitdiff_plain;h=fba506c87ca0af65b92f98855127b613085eb66e;p=ppam-mpi.git readme.md --- diff --git a/README.html b/README.html deleted file mode 100644 index d80a345..0000000 --- a/README.html +++ /dev/null @@ -1,17 +0,0 @@ -

Parallel clustering with a k-medoids algorithm

- -

Joint work with Jairo Cugliari.

- -
- -

This C program runs the k-medoid algorithm on several subsets of one (presumably big) dataset. -The computed medoids are then merged iteratively, until we get a final set of k centers.

- -
- -

The folder "communication/" contains latex sources (and generated pdf files) of a short paper submitted -to the Journées de Statistique in Rennes, France (2014), and also the slides presented at this event.

- -

The other folder contains all the C code; but not the EDF (french electricity company) datasets, because they -are not public. Since the (de)serialization process in code/src/TimeSeries/ is tailored for these data, -it is necessary to adapt this small part of the code to use any other custom time-series files.

diff --git a/README.md b/README.md new file mode 100644 index 0000000..103665d --- /dev/null +++ b/README.md @@ -0,0 +1,17 @@ +# Parallel clustering with a k-medoids algorithm + +Joint work with [Jairo Cugliari](http://eric.univ-lyon2.fr/~jcugliari/) + +--- + +This C program runs the k-medoid algorithm on several subsets of one (presumably big) dataset. +The computed medoids are then merged iteratively, until we get a final set of k centers. + +--- + +The folder "communication/" contains latex sources (and generated pdf files) of a short paper submitted +to the Journées de Statistique in Rennes, France (2014), and also the slides presented at this event. + +The other folder contains all the C code; but not the EDF (french electricity company) datasets, because they +are not public. Since the (de)serialization process in code/src/TimeSeries/ is tailored for these data, +it is necessary to adapt this small part of the code to use any other custom time-series files.