Scripts for training a model to assess personalized cancer risks.

Convert raw data from web to CSV file.

raw_to_csv.py

Select and modify features based on manual curation and missing data.

preprocessing.py

Scale numerical data, convert categorical data to binary data.

transformation.py

Train model using stochastic gradient descent (logistic regression and linear SVM), logistic regression, and kernel approximation + linear SVM.

learning_SGD.py
learning_LR.py
learning_kernel.py