[mlpack] GSoC 2014 : Introduction and Interests

[Ryan Curtin]

On Thu, Mar 13, 2014 at 03:35:55PM +0530, Anand Soni wrote:
> Hi Marcus,
> 
> I have decided on the metrics to be implemented. Mostly, I will be
> implementing and testing with the following metrics :
> 
> a) Accuracy
> b) F-measure
> c) Lift
> d) Precision
> e) Recall
> f) Matthews correlation coefficient (turned about to be a good
> suggestion from you)
> g) Mean Squared error
> h) Mean predictive information (very similar to cross entropy, but
> more easily interpreted)
> 
> So, there are 8 metrics in total. The last two are probabilistic
> measures. I will talk about these metrics in detail in the proposal.
> Please tell me if you want something to be added or removed.

I would like to know if your code will be flexible enough to support
additional metrics that may be added in the future.  If it's not, that
is something to consider.

> Also, does mlpack already has a classifier based on feed-forward
> neural networks and the backpropagation algorithm? If not and if time
> permits, I would like to add it as a classifier for mlpack.

No, it does not; if you are interested in adding this, let's make sure
it is faster than competing implementations, either through careful
implementation, or by implementing a more efficient algorithm.

-- 
Ryan Curtin    | "Here... there... what's the difference?"
ryan at ratml.org |   - Prisoner