Project 4 Perceptrons README

To compile and run the code for this submission, simply run the following command in terminal
$ python main.py
Ensure your Python version is 3.7.5 or later.

Explanation of program:

Perceptron.py:
    - implements the perceptron as a class
    - perceptron has member data called weights which holds the weights <w_0...w_n>
    - also has member function o which takes inputs and calculates output 1 or -1

main.py:
    - implements function used to gather data from iris.data file
    - implements and runs the perceptron training rule on the training data
    - prints out the results of the learning algorithm
    - learning constant is set below perceptron training rule function

Review of Deliverable:

D1 - Source Code
    * main.py 
    * Perceptron.py

Running the main program will produce the following output files, meeting each deliverable requirement:

D2 - Epoch stats files and plot files for Task 2:
    * T2_stats.txt and T2_Iris-setosa.pdf
    * T2_stats.txt and T2_Iris-versicolor.pdf
    * T2_stats.txt and T2_Iris-virginica.pdf

D3 - Epoch stats files and plot files for Task 3:
    Task 3.1:
        * T3.1_stats.txt and T3.1_Iris-setosa.pdf
        * T3.1_stats.txt and T3.1_Iris-versicolor.pdf
        * T3.1_stats.txt and T3.1_Iris-virginica.pdf
    Task 3.2:
        * T3.2_stats.txt and T3.2_Iris-setosa.pdf
        * T3.2_stats.txt and T3.2_Iris-versicolor.pdf
        * T3.2_stats.txt and T3.2_Iris-virginica.pdf
    Task 3.3:
        * T3.3_stats.txt and T3.3_Iris-setosa.pdf
        * T3.3_stats.txt and T3.3_Iris-versicolor.pdf
        * T3.3_stats.txt and T3.3_Iris-virginica.pdf

D4 - Epoch stats files and plot files for Task 4:
    Task 4.1:
        * T4.1_stats.txt and T4.1_Iris-setosa.pdf
        * T4.1_stats.txt and T4.1_Iris-versicolor.pdf
        * T4.1_stats.txt and T4.1_Iris-virginica.pdf

All the files ending in "_stats.txt" specify the task number they satisfy in the name of the file and contain the epoch #, # of errors on training data for that epoch, and current weight vector for each of the three LPs from the beginning of the algorithm to the end. 
All the file ending in "_Iris-setosa.pdf", "_Iris-versicolor.pdf", and "_Iris-virginica.pdf" specify the task number they satisfy in the name of the file and contain the graphs showing the # of errors made for each epoch of learning on the y axis versus the epoch # of learning on the x axis for each of the respective flowers.

The final deliverables,

D5 - Write Ups
    * T5.1.txt - answers task 2 question and analyses task 2 results
    * T5.2.txt - analyses task 3 results
    * T5.3.txt - analyses task 4 results

D6 - Write up reflecting on project
    * project_reflection.txt

D7 - README file
    * This file serves as the README