Back to search
Top Contributors
19
commits
This repository demonstrates the use of Logistic Regression, Random Forest, and XGBoost for breast cancer classification. It covers data preprocessing, hyperparameter tuning, and model evaluation with ROC-AUC and SHAP values, showcasing key skills in healthcare data analytics.
Stars
2
Forks
1
Watchers
2
Open Issues
0
Overall repository health assessment
No package.json found
This might not be a Node.js project
19
commits
Update and rename breast_cancer_diagnosis_annotated_code.py to Breast_Cancer_Diagnosis_ML_code.py
358c70eView on GitHub