[ppam-mpi.git] / README.html

<h1>Parallel clustering with k-medoids algorithm</h1>

<p>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.</p>

<hr/>

<p>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.</p>

<p>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.</p>
Commit	Line	Data
70b2e106 BA	1	<h1>Parallel clustering with k-medoids algorithm</h1>
	2
	3	<p>This C program runs the k-medoid algorithm on several subsets of one (presumably big) dataset.
	4	The computed medoids are then merged iteratively, until we get a final set of k centers.</p>
	5
	6	<hr/>
	7
	8	<p>The folder "communication/" contains latex sources (and generated pdf files) of a short paper submitted
	9	to the Journées de Statistique in Rennes, France (2014), and also the slides presented at this event.</p>
	10
	11	<p>The other folder contains all the C code; but not the EDF (french electricity company) datasets, because they
	12	are not public. Since the (de)serialization process in code/src/TimeSeries/ is tailored for these data,
	13	it is necessary to adapt this small part of the code to use any other custom time-series files.</p>