Prostate Dataset
Exploratory statistical study and predictive modelling on a clinical prostate dataset, focusing on the relationship between anatomical covariates and a key antigen marker.
Implements dimensionality reduction via Principal Component Analysis (PCA) alongside simple and multiple linear regression models, accompanied by an interactive Streamlit application to inspect projections and residuals.
Stack
- Python
- scikit-learn
- NumPy
- Matplotlib
- Streamlit