On 1/2/06, John Gant <[EMAIL PROTECTED]> wrote: > Reviewed the specification, and can say that it seems to contain some > nice algorithms. I think [math] could add some very important > methodologies for time series analysis (for instance smoothing > algorithms, AR, MA, ARMA (if desired), and other decomposition > methodologies). Phil, how can [math] contribute to this specification?
I am still studying the spec, so can't yet comment fully, but in general, I can see two ways for us to get involved: 1. Contribute to the spec itself - i.e., give feedback on the structure and content of the API 2. Implement portions of the spec or provide wrappers for [math] components that provide some of the functionality described by the spec The comment period for the "Early Draft Review" closes 11 Jan, so if we want to get involved in 1., we should start that ASAP. My only general comment so far is that because the actors targeted by the spec appear to be essentially "datamining vendors" and "API users" there is not as much mix-and-match pluggability in the API as we might like to see in [math] - i.e., "vendors" like us who want to provide pluggability at multiple levels may not have the flexibility that we would like. This is just based on a very preliminary review, however, and I may change my mind about this when I have worked more with the API and more fully digested the spec. > Noticed that the distance measures (within clustering algorithms) are > pluggable but didn't see a list of distance measures in this spec, > should [math] create or contribute to this list? This is a good example illustrating how we should be thinking about the spec. The first question to ask is is the API sufficient to provide all of the implementation flexibility that the various clustering algorithms are going to need? We discussed this same topic a while back. Assuming the answer is "yes" then no feedback is necessary (for that part of the spec) and we can plow ahead creating some distance measure implementations - the latter would be part of our "vendor implementation". The benefit of taking this approach is that our metrics would then become (independently) useful to a broader audience than our own clustering implementations (as would the clustering impls themselves, if they implement the spec API). Phil --------------------------------------------------------------------- To unsubscribe, e-mail: [EMAIL PROTECTED] For additional commands, e-mail: [EMAIL PROTECTED]
