Machine learning techniques have become widely used for medical diagnosis. This model uses a simple XGBoost to predict whether tumors presented in the dataset are malignant or benign. The Breast Cancer Wisconsin (Diagnostic) Data Set was used with an 80/20 train-test split. On the test set, the model predicted the nature of tumors 95.61% accurately with an F1 Score of 0.94.
The code was adapted from the Deep Learning A-Z 2023 course on Udemy.
From the root folder of the project, run
./install.sh
to create the virtual environment and install the dependencies. Then, run ./run.sh to execute the run file.