began naive random government. need to look into speeding up the deliberation process.
benchmarked various implementations.
rewrote naive random_gov to take advantage of data.table and parallelization.
changed internal distance calculation to include base::dist(), and added vanilla accuracy gauge to trainRandomHouse().
fixed error in training function, and made benchmarking function.
cleaned up dt_centric_random_gov for use on grizzlybear.
implemented metascore-based elections and testRandomHouse function, and updated benchmark function accordingly.
cleaned up dt_centric_... for use on grizzlybear, and allowed for different methods in base::dist() to be used.
merged in changes to load_data from master.

Merge branch 'master' into random_gov

Conflicts:
	R/load_data.R
made a serial, knn-based implementation of random_gov. Need to rework metascore to something like maximum likelihood.
revamped metascoring to allow for "proportions" to be used in elections. (proportions are just estimates of P(Y=k | Psi(X)=k).)
changed probMetaScoreWinner to sample according to the approximate posterior likelihoods -- does not help accuracy.
implemented selective government build which tries to make one committee per lable, with posterior likelihood greater than a desired threshold.
tidy'd up code, and added class.width parameter to selectiveBuildRoutine.
did some minor refactoring of buildRandomGov to allow for variable class.width.
implemented "binary" distance in knn prediction, and allowed for sampling with replacement inside buildRandomGov. Setup argument matching for "method" and "dist" arguments.
wrapped up selectiveBuildTrainPredict into buildTrainPredict and cleaned up issues related to trainRandomGov.
added foreach() capability in predict...
set.seeds wherever sample() is used to ensure reproducibility, and implemented cross-validation scheme for "vanilla" voting method with parallelization options at the various levels.
prepared cross-validation script for use on grizzlybear.