5 papers
Federated Rule Ensemble Method in Medical Data
Ke Wan, Kensuke Tanioka, Toshio Shimokawa
Machine learning has become integral to medical research and is increasingly applied in clinical settings to support diagnosis and decision-making; however, its effectiveness depen…
Principal component-guided sparse reduced-rank regression
Kanji Goto, Shintaro Yuki, Kensuke Tanioka +1
Reduced-rank regression estimates regression coefficients by imposing a low-rank constraint on the matrix of regression coefficients, thereby accounting for correlations among resp…
Regularized Sparse Optimal Discriminant Clustering
Mayu Hiraishi, Kensuke Tanioka, Hiroshi Yadohisa
We propose a new method based on sparse optimal discriminant clustering (SODC), incorporating a penalty term into the scoring matrix based on convex clustering. With the addition o…
Causal rule ensemble approach for multi-arm data
Ke Wan, Kensuke Tanioka, Toshio Shimokawa
Heterogeneous treatment effect (HTE) estimation is critical in medical research. It provides insights into how treatment effects vary among individuals, which can provide statistic…
Wilcoxon-type Multivariate Cluster Elastic Net
Mayu Hiraishi, Kensuke Tanioka, Hiroshi Yadohisa
We propose a method for high dimensional multivariate regression that is robust to random error distributions that are heavy-tailed or contain outliers, while preserving estimation…