Date: 12/16/18
Authors: 
	Adam Ali 101004367
	Nicolas Perez 100978917

Source Files:
In each directory you will find jupyter notebook files and their corresponding equivalent 
python files with the same name. Here is a list of files and what they do:

MixtureOfExperts/K-means.py - Computes K-means clusters and labels for all the training data
for each k-fold. It also saves these clusters and labels along with the time required to
compute them for each fold in numpy arrays saved inside .npy files. By default it computes
clusters for the number of clusters equal to 2 all the way to 10.

EnsembleMethod/EnsembleMethodMLP.py - runs the ensemble method on a range of number of models
from 2 to 10 for 3 epochs and then saves the accuracy and time to train in .npy files. 
Parameters can be changed inside the python file from lines 65 to 79 to adjust epochs, number
of k-folds, and number of models trained.

MixtureOfExperts/MixtureOfExpertsMLP.py - runs mixture of experts on a range of number of models
from 2 to 10 for 3 epochs and then saves the accuracy and time to train in .npy files. 
Parameters can be changed inside the python file from lines 66 to 77 to adjust epochs, number
of k-folds, and number of models trained.

1EpochResults.py - Reads the test results generated from experiments after 1 epoch and plots 
them using matplotlib.

3EpochResults.py - Reads the test results generated from experiments after 3 epochs and plots 
them using matplotlib.

Operating Instructions:
Each of these files can be ran by typing in: python filename.py
inside of a command prompt terminal while inside the directory for that file. Saved files for
displaying graph results will not be overwritten except for in the case of running the 
K-means.py file.