Personalized Medicine Kaggle Competition
This notebook describes my approach to the Kaggle competition named in the title. This was a research competition at Kaggle in cooperation with the Memorial Sloan Kettering Cancer Center (MSKCC). The goal of the competition was to create a machine learning algorithm that can classify genetic variations that are present in cancer cells. Tumors contain cells with many different abnormal mutations in their DNA: some of these mutations are the drivers of tumor growth, whereas others are neutral and considered passengers. Normally, mutations are manually classified into different categories after literature review by clinicians. The dataset made available for this competition contains mutations that have been manually anotated into 9 different categories. The goal is to predict the correct category of mutations in the test set. ...