On Sat, 13 Aug 2016 03:59:44 +0300, Artem Barger wrote:
Hi,
I was thinking of adding a few additional demo application for user
guide
page:
1. Seeding algorithm for kmeans++ (sampling centers based on the
distances).
2. Non uniform coreset for kmeans clustering (importance sampling),
reducing big data into small based on random algorithm.
At first sight, it looks like one would have to understand "kmeans"
in order to understand how to use a dead simple API...
What is the reasonable amount of demo applications for user guide
which
should be enough to start with?
It depends on the library, I guess.
Large libraries would probably need more examples.
In the case of Commons Rng, I'm still waiting for comments from
people who were, supposedly, relying critically on top performance...
Regards,
Gilles
Best regards,
Artem Barger.
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