This program applies Genetic Algorithm to predict a class of breast cancer that are "Malignant" and "Benign" by using Wisconsin Diagnostic Breast Cancer (WDBC) Dataset.
This program provides flexible ways for users to adjust mutation proability, number of generations, number of hidden layers in neural network, and number of nodes in each hidden layer.
The output will be provided on the terminal and an exported output file. Users can arbitrarily adjust file name by typing on the terminal when the program asks for file name.
This program consists of 2 main parts that are ga.py and process.py.
In ga.py, it provides main functions for this program(i.e. cross-validation, iterating thorugh generations, cross-over, mutation), and process.py provides functions to support ga.py such as sigmoid function, separating data, asking for input, feature scaling, and individuals creation.
This program is used only for educational purpose. This program is initially created on the basis of educational purpose to simulate and analyze process of genetic algorithm.
python ga.py