2 papers
stat.ML2025
Lassoed Forests: Random Forests with Adaptive Lasso Post-selection
Jing Shang, James Bannon, Benjamin Haibe-Kains +1
Random forests are a statistical learning technique that use bootstrap aggregation to average high-variance and low-bias trees. Improvements to random forests, such as applying Las…
stat.ME2025
Pre-validation Revisited
Jing Shang, Sourav Chatterjee, Trevor Hastie +1
Pre-validation is a way to build prediction model with two datasets of significantly different feature dimensions. Previous work showed that the asymptotic distribution of the resu…