I'm interested in joining the team. I looked at the Kaggle contests and I
agree that the best choice would be Solar Energy Prediction, but I wouldn't
discount the Phone accelerometer contest. I think its a good fit for the
CLA and and interesting application. The forum posts for that contest seem
to indicate the sponsors are willing to judge a 'clean' (no leakage)
version of the contest.


On Thu, Oct 17, 2013 at 10:45 AM, Jay Gokhale <[email protected]> wrote:

> I'd love to use CLA's on a kaggle project!
>
> If Chetan's description is correct, it seems to me that the Solar Energy
> Prediction contest would be the most straight forward one to work on.
>
> Jay Gokhale
>
>
> On Wed, Oct 16, 2013 at 9:07 PM, Matthew Taylor <[email protected]> wrote:
>
>> These also sound like good hackathon projects!
>>
>> Matt
>>
>> Sent from my MegaPhone
>>
>> On Oct 16, 2013, at 8:03 PM, Chetan Surpur <[email protected]> wrote:
>>
>> I'm interested in participating!
>>
>> I haven't decided on one yet, but I wanted to point out that the CLA
>> looks ideally suited for the AMS 2013-2014 Solar Energy Prediction
>> contest. From what I can tell, it's about predicting the daily energy
>> output of solar farms from 12, 15, 18, 21, 24-hourly training data. There's
>> 29 days to go.
>>
>>
>> On Wed, Oct 16, 2013 at 7:31 PM, Pedro Tabacof <[email protected]> wrote:
>>
>>> Hello,
>>>
>>> After the warm reception of the Kaggle competition idea, I decided to
>>> create the thread asap. For those who are not aware, Kaggle is a data
>>> mining competition website. It has been hyped on the machine learning media
>>> and has some great people participating in it. It rewards with different
>>> prizes, but my focus is not earn money, but rather to see how good NuPIC
>>> would fare against the state of the art. I found those following
>>> competitions to be a viable start:
>>>
>>> 1) Accelerometer Biometric Competition
>>> From real acceleration data you have to guess from which cell phone came
>>> the test samples.
>>> 36 days to go
>>> Pros:
>>> -Multivariable, temporal data seems ideal for the CLA
>>> Cons:
>>> -The best competitors are using data leaks (meta-information), so the
>>> chance of winning fairly is zero (though they will give a consolation prize
>>> to the best "honest" entry)
>>> Questions:
>>> -How fast would NuPIC go through a 1GB CSV file?
>>> -The test data is not open-ended, that is, you have to say whether a
>>> recording belongs to a specific cell phone or not, with 50% chance of being
>>> right. Would NuPIC do well in this case?
>>>
>>> 2) Multi-Label Bird Species Classification
>>> Try to guess the bird species present on some audio recordings
>>> 38 days to go
>>> Pros:
>>> -Temporal data
>>> Cons:
>>> -Multiple labels, so I think we would need 87 different models, which is
>>> kinda impractical
>>> Question:
>>> -Is there a better way to do multi-label classification with NuPIC?
>>>
>>> 3) Conway's Reverse Game of Life
>>> Reverse the game of life for 1 to 5 steps
>>> 4 months to go
>>> Pros:
>>> -Natural input sparseness (have to check on it)
>>> -Temporal data
>>> -Multistep classification
>>> -We can generate our own training data if necessary
>>> Cons:
>>> -Maybe there are very straightforward ways to solve this (rule based,
>>> brute force, etc)
>>> -Too much time before the competition ends
>>> Questions:
>>> -How sparse does the input need to be for the CLA to work well?
>>> -Is it possible to use a 2D arrangement on the cells connection matrix?
>>>
>>> There is also the AMS 2013-2014 Solar Energy Prediction contest, but I
>>> didn't have time to go over it. The other competitions don't seem to be
>>> suited for NuPIC.
>>>
>>> Who here is interested on participating and what competition do you
>>> think to be the most promising one?
>>>
>>> Pedro.
>>> --
>>> Pedro Tabacof,
>>> Unicamp - Eng. de Computação 08.
>>>
>>> _______________________________________________
>>> nupic mailing list
>>> [email protected]
>>> http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org
>>>
>>>
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