Project 2- FYS-STK4155-Applied Machine Learning an data analysis

Description

Classification and Regression, from linear and logistic regression to neural networks

src/ffnn.py: Class containing the feed forward neural networks
src/logistic_reg.py: Class containing the logistic regression functions
src/utils.py: Utillity functions like activation functions and such
src/logeg_predict.py: Performing logistic regression on the Wisconsin breast cancer dataset. To run the functions, scroll down to the bottom of the script and remove the hashtag in front of function to run.
src/franke.py: Script containing Frank's function. Is used to produce the dataset in the regression case.
src/sgd_predict.py: Performing regression on Franke's dataset by using the SGD method in OLS and Ridge.
src/franke_results/franke_predict.py: Performing regression on Franke´s dataset by using the neural network.
src/mnist_results/mnist_predict.py: Performing classification on the MNIST dataset by using the neural network.