New Object Early Community Build #3 and 4-5-6: FluidDataSeries, and DTW-based classification and regression - NOW IN SC TOO

[rodrigo.constanzo]

@tremblap

be aware that now it is brute force, so large corpora might be a problem. @lewardo had plans of doing fast dtw and might still be able to do it if I manage to convince him of the benefits of volunteering (or if you bribe him)

I’ve not tested anything with this, but I remember back when doing entrymatcher vs fluid.kdtree~ comparisons (thread) the bruteforce was still quite performant until things got really really big (with the KDTree being faster only above a certain size). (actually revisiting that thread brute force was faster nearly all the time, up to 200k entries which is as far as I tested from the looks of it).

@tremblap

LSTM is on its way for that.

Ooh, nice. I can see that being useful for some of the time stuff I was trying to work out a while back (predicting time series).

@tremblap

you could implement a running gesture query - this is just one example. dataseries allow you to add and remove items at various positions, so you could have a rolling thing. I plan to code one soon-ish as demo

Yeah I had a quick poke at this but there’s a bunch I don’t understand about the interface yet and kind of moved onto the next example.

@tremblap

thanks - it is hacky indeed. but did the comparison with dataset (in 1) and with knnreg/class in 3/2 helped to understand?

I always prefer contextual examples rather than didactic ones, so I definitely understood after examples 2/3, though those both had the “press one, now press two, not press three, now press four” bouncing around thing which is harder to follow.