The interface with my GP classifier is very simple; to run it on a given dataset (in .csv format), simply type: python gpclassifier.py [filename]

I have provided the three datasets I used throughout my project - there are many others from the UC Irvine Learning Repository, but a lot of them need some tweaking to the formatting. The three included files are: iris.csv (classifying irises based on some attributes) credit.csv (classifying credit applicants as suggested or not) pimadiabetes.csv (classifying people as diabetes patients based on various symptoms/attribtues)

All parameters that the user may want to alter can be found at the bottom of the gpclassifer.py file.