Loading view.
PhD Speaking Qualifier
Enhancing Model Performance and Interpretability with Causal Inference as a Feature Selection Algorithm
NSH 1305Abstract: Causal inference focuses on uncovering cause-effect relationships from data, diverging from conventional machine learning which primarily relies on correlation analysis. By identifying these causal relationships, causal inference improves feature selection for predictive models, leading to predictions that are more accurate, interpretable, and robust. This approach proves especially effective with interventional data, such as randomized [...]