[ml] KDD cup submission status

Mike Schachter mike at mindmech.com
Fri Jun 4 20:42:34 UTC 2010

So it's taking about 9 hours to create a graph from a 4.4GB file, I'm
going to work on improving the code to make it a bit faster, and also
am investigating a MapReduce solution.

Basically the clustering process can be broken down into two stages:

1) Construct the graph, apply the clustering algorithm to break graph into
2) Apply the clustered graph to the data again to classify each skill set

I'll keep working on it and let everyone know how things are going with it,
as I mentioned in another email, the source code is in our new sourceforge
project's git repository.


On Thu, Jun 3, 2010 at 7:48 PM, Mike Schachter <mike at mindmech.com> wrote:

> Sounds like you're making great progress! I'll be working on the
> graph clustering algorithm for the skill set tonight and will keep
> you posted on how things are going.
>   mike
> On Thu, Jun 3, 2010 at 6:17 PM, Andreas von Hessling <
> vonhessling at gmail.com> wrote:
>> Doing a few basic tricks, I catapulted the submission into the 50th
>> percentile.  That is not even running any ML algorithm.
>> I'm planning on running the NaiveBayesUpdateable classifier
>> (http://weka.wikispaces.com/Classifying+large+datasets) over
>> discretized IQ/IQ strength/Chance/Chance strength from the command
>> line to evaluate performance.  Another attempt would be to load all
>> data into memory (<3GB, even for full Bridge Train) and run SVMlib
>> over it.
>> If someone wants to try MOA
>> (http://www.cs.waikato.ac.nz/~abifet/MOA/index.html<http://www.cs.waikato.ac.nz/%7Eabifet/MOA/index.html>),
>> this would be
>> helpful also in the long run (at least a tutorial how to set it up and
>> run).
>> The reduced datasets plus the IQ values are linked on the wiki: Features
>> are:
>>   ...> row INT,
>>   ...> studentid VARCHAR(30),
>>   ...> problemhierarchy TEXT,
>>   ...> problemname TEXT,
>>   ...> problemview INT,
>>   ...> problemstepname TEXT,
>>   ...> cfa INT,
>>   ...> iq REAL
>> IQ strength (number of attempts per student) should be available soon.
>>  (perhaps add'l features will become available as well)
>> I'm still hoping somebody could cluster Erin's normalized skills data
>> and provide a row -> cluster id mapping for algebra and bridge train
>> and test sets (I don't have the data any more).
>> Andy
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