Add arguement parser and feature subset sampling
Added paper annotations for clarity

-made differential weight (F) a default parameter for mutate function
-added annotations to help clarify DE mutation logic
Add documentation
Updated yHat computation and formatting

-removed unneeded whitespace
-updated yhat computation to perform prediction computation for each
observation instead of entire population at once.  This may help resolve
what was causing predicted values to be the same as observed values
Reset tracking of training SEE to training SDEP
Analyze data using Pandas library.
To run ipython notebook in browser, command: ipython notebook --pyblab=inline
Add try block in findNewPopulation.
Correct error in findFitnessOfARow.
Use data functions in FromData file instead.
add gradient descent functions
add pycallgraph for performance analysis visualization
add main testing function and pycallgraph for permormance analysis
clean up, flow organization
don't print in cv_predict
rename files to reflect ANN, not MLR
Decision tree for HIV data using sklearn
Remove question
Split data. Train and validate
Working MLR-BPSO implementation