Update README.md

Author: maillouxc

README.md

@@ -1,2 +1,59 @@
 # datamining-project
 This is a project for FGCU's knowledge discovery and data mining course.
+It focuses on spam email classification.
+
+Part 1 of the project is an implementation of a spam email classifier from scratch in Java 8,
+using a Naive Bayes classifier, and also a K-nearest-neighbors classifier.
+
+Part 2 of the project is a pair of experiments in Scikit learn with various other algorithms.
+
+## Run instructions:
+
+### Ensure that the dataset meets the following criteria:
+ - All files must be .txt files
+ - All files must be stored alone in their directory with no other files
+ - All files be divided between two subdirectories, `test` and `training`
+ - All spam emails are expected to have a filename beginning with "sp"
+
+### Usage:
+
+ Part 1:
+ 
+ ```
+ usage: Classify 
+ data_path
+ algorithm_name (Either "knn" or "naivebayes")
+ [k] The K value to use - only used if algorithm is "knn"
+ ```
+ 
+ Part 2:
+ 
+ ```
+ usage: python experiments.py
+ 
+ There are no arguments - the program is merely a script which conducts experiments with various values.
+ ```
+ 
+ 
+### Run instuctions:
+
+Part 1:
+
+ 1. Ensure that you have Java JRE 8 installed.
+ 2. Compile the program using Gradle:
+ (From the project's part1 subdirectory)
+ `./gradlew build`
+ The generated Java class files will then be in the /build/classes/java/main directory.
+ (The program can also be compiled like a standard java program if this has problems).
+ 3. Run the program as `java Classify arguments`
+ The arugments are described in the above section
+
+Part 2:
+
+ 1. Ensure that you have Python 3.7 or greater installed.
+ a. If you have _both_ Python 2 and Python 3 installed, you will need to ensure you run the program using `python3`.
+ 2. Ensure that you have pip installed.
+ b. If you have _both_ Python 2 and Python 3 installed, you will need to run pip commands using `pip3`.
+ 3. Install scikit-learn: `pip install sklearn`
+ 4. Install numpy: `pip install numpy`
+ 5. Run the program as: `python experiments.py path_to_data`