[ml] wiimote libsvm experiments
Michael C. Toren
mct at toren.net
Wed Jun 17 18:19:42 PDT 2009
I sadly didn't have time this week to dive into Hidden Markov models, but
I was able to massage the data a little in order be able to run libsvm on
it directly. I was really curious to see if just libsvm by itself would
be enough to make sense of the data.
I ended up with some perl code that sorted the data by time, then slotted
each datapoint into a fixed number of buckets. For buckets that had more
than one datapoint, I took the mean. For buckets with no datapoint, I
assumed a linear progression from its neighbors. For each experiment, I
randomly selected 75% of the data to use for training, and used the
remaining 25% to test my accuracy against. I experimented with changing
two knobs -- the kernel function used by svm-train (0..3), and the number
of buckets I placed data in (10, 50, 100, and 1000).
The results:
Kernel 0 Kernel 1 Kernel 2 Kernel 3
-------- -------- -------- --------
10 Buckets: 96.875% 54.6875% 87.5% 93.75%
50 Buckets: 83.908% 60.9195% 97.7011% 100%
100 Buckets: 98.5507% 71.0145% 98.5507% 100%
1000 Buckets: 98.4615% 63.0769% 100% 93.8462%
Some of those results look *really* promising, although I wonder if svm
is going to hold up when we introduce more complicated gestures...
-mct
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