This repository contains the coursework for the Data Science & Information Technologies masters course: Machine Learning in Computational Biology at the National and Kapodistrian University of Athens (NKUA) during the Spring 2023 semester
In this paper we use the nested cross validation method in order to fine tune and test the perfomance of 5 machine learning algorithms, namely Support Vector Machines, Linear Regression, Gaussian Naive Bayes and Linear Discriminant Analysis, on the Hepatitis C dataset. After fine tuning the algorithms we select the one with the best perfomance on the dataset and we evaluate several perfomance metrics on the dataset.
The Hepatitis C dataset is an openly available dataset which consist of 14 attributes
- Project Report
- Nested-cv python notebook