Our main contribution is to extend recently developed selective inference framework for linear models to high-order interaction models by developing a novel ...

Jun 28, 2022 · We consider the sparse high-order interaction model as an interpretable and reliable model with a good prediction ability. However, finding ...

Abstract. Finding statistically significant high-order interactions in predictive modeling is important but challenging task because the possible number of high ...

In this paper we study feature se- lection and statistical inference for sparse high- order interaction models. Our main contribution is to extend recently ...

Jun 9, 2021 · Abstract:Automated high-stake decision-making such as medical diagnosis requires models with high interpretability and reliability.

The main contribution is to extend recently developed selective inference framework for linear models to high-order interaction models by developing a novel ...

A method combining predictive pattern mining (itemset, sequence) using a linear model with L1 regularization and statistical hypothesis test considering ...

Selective Inference for Sparse High-Order Interaction Models. Suzumura S et al. Proceedings of machine learning research. 2017; 70:3338-3347. Show Details.

We consider the sparse high-order interaction model as an interpretable and reliable model with a good prediction ability. However, finding statistically ...

We consider the sparse high-order interaction model as an interpretable and reliable model with a good prediction ability. However, finding statistically ...