This is a Machine Learning project developed in Python that aims at predicting the class of breast tumor (benign or malignant) given certain characteristics of the patients samples. The data is taken from the Wisconsin Breast Cancer Database, whose specific info are provided by the repository.
The models exploited in this project are: Logistic Regression (along with Lasso features selection), Linear Discriminant Analysis, Quadratic Discriminant Analysis, K-Nearest-Neighbors and Support Vector Machines (Maximal MArgin Classifier, Support Vector Classifier and Support Vector Machine). The models were developed mainly thanks to the corresponding scikit-learn modules.
Here I public a commented Jupyter Notebook, which includes the pre-processing of the data and a comparison of all the exploited models to identify the best one for the task.