1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 1 cited
Feature Importance Measurement based on Decision Tree Sampling
Chao Huang, Diptesh Das, Koji Tsuda
Random forest is effective for prediction tasks but the randomness of tree generation hinders interpretability in feature importance analysis. To address this, we proposed DT-Sampl…
stat.ML2022★ 1 cited
A Confidence Machine for Sparse High-Order Interaction Model
Diptesh Das, Eugene Ndiaye, Ichiro Takeuchi
In predictive modeling for high-stake decision-making, predictors must be not only accurate but also reliable. Conformal prediction (CP) is a promising approach for obtaining the c…
stat.ML2021
Fast and More Powerful Selective Inference for Sparse High-order Interaction Model
Diptesh Das, Vo Nguyen Le Duy, Hiroyuki Hanada +2
Automated high-stake decision-making such as medical diagnosis requires models with high interpretability and reliability. As one of the interpretable and reliable models with good…