Dimension reduction, State, Orientation, and Velocity.
Got a late start in the office today, so as soon as I get in I got my gear on for a brain cleaning ride. Pushed really hard today, and combined with some nice weather and low traffic hit my first 16+ average MPH door-to-door. Landed a 16.4 mph average, and felt really proud of it.
Focus today was on learning some more about Manifold learning and its applications for reduction of high dimensional data for unsupervised learning.
SciKit includes some great documentation and resources including a working sample comparing various Manifold learning techniques against test data sets.
My goal now is to take the sorted data_generator.py code from yesterday and compare the manifold learning examples against the clustered output of the unreduced data. Once I have a benchmark set up I can do the same for the sample live data.
The output of the SciKit examples in MatPlotLib is really attractive as well.