Add a new plot for plotting all the errors in a bar chart
Update plotting to allow plotting errors feature wise and method wise
Add randomization to kfolds to reduce the overall STDEV of the errors
Remove "tuned" feature vectors
Add storing results in a large dict so it can later be plotted
Remove old neural net comments
Start parallelizing cross_clf_kfold
Add results for 1024 fingerprint feature
Make test_clf_kfold parallel
Set number of processes per pool to the min of number of work and cores
Add results for 1024 fingerprint feature
Add toggle for doing parallel calculations at cross validation and test
Remove test kfolds parallel code

This is because doing the parallelism at the cross validation level
is much more efficient.
Merge branch 'parallel'
Expand search range for k-NN and Tree
Cleanup utils.py
Add some more comments to the utils code so it is easier to understand
Update results.txt to include results for coulomb and fingerprints
Change kfolds functions to only return test errors
Add some docstrings to the functions in utils