[mlpack] Automative benchmarking

[Marcus Edel]

Hello Shree.

Great that you're interested in working on the automatic benchmarking project!

> 1.Given a specific time frame ,which is the fastest running time.
> 2.Benchmarking in distributed environment.
> Also,I feel that the benchmarking scripts can also be extended to classification algorithms like SVM,Bayesian as well.

We can definitely expand the benchmark system in this direction. The tricky part is to visualize everything in a good manner. I like the suggestion from the shogun description to use d3js (take a look at the examples):

https://github.com/mbostock/d3/wiki/Gallery

> It would be really nice if you could give a clear idea about the integration with Shogun in this project.

As pointed out in their project description, the main task will be focused on implementing a way to compare the accuracy of the algorithms (like you suggested), adding more shogun algorithms to the comparison and fix potential bottlenecks. I think that's just a one line summary of their description:

http://www.shogun-toolbox.org/page/Events/gsoc2014_ideas#mlpack

Anyway, maybe you can tell us which part you like to discuss in more detail.

Thanks,
Marcus


On 04 Mar 2014, at 14:08, Ranjani <shreeranjaniss at gmail.com> wrote:

> Hi,
> I am Shree Ranjani ,a final year Computer Science student from India.
> 
> I am really interested in continuing the work on "Automative benchmarking of mlpack methods".
> I have been playing around with mlpack libraries quite a bit and also ran benchmarking scripts for some algorithms.I have been going through the discussions on this project and find that the following ideas should be given more priority more than others
> 
> 1.Given a specific time frame ,which is the fastest running time.
> 2.Benchmarking in distributed environment.
> Also,I feel that the benchmarking scripts can also be extended to classification algorithms like SVM,Bayesian as well.
> 
> It would be really nice if you could give a clear idea about the integration with Shogun in this project.
> 
> Mentioning more about myself - I am pretty comfortable writing codes in Python,C++. I have done a research internship in NetApp,India on a machine learning project.
> I am really interested in Machine learning ,Data Mining and NLP and all my academic projects were in this area.Some of them are
> 1.Developed an Intelligent Classroom system that automated subjective question and answer evaluation and provided feedback to teachers about students’ performance
> 2.Working on Strength of Sentiment analysis of movie data using NLP techniques
> I have taken up courses on Artificial Intelligence,Data Mining and Machine learning during my course curriculum.
> 
> 
> Do let me know,so that i can start working asap! :)
> 
> -- 
> Regards,
> Shree Ranjani 
> 
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> mlpack at cc.gatech.edu
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