DeepAI AI Chat
Log In Sign Up

Fast and More Powerful Selective Inference for Sparse High-order Interaction Model

06/09/2021
by   Diptesh Das, et al.
0

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 prediction ability, we consider Sparse High-order Interaction Model (SHIM) in this study. However, finding statistically significant high-order interactions is challenging due to the intrinsic high dimensionality of the combinatorial effects. Another problem in data-driven modeling is the effect of "cherry-picking" a.k.a. selection bias. Our main contribution is to extend the recently developed parametric programming approach for selective inference to high-order interaction models. Exhaustive search over the cherry tree (all possible interactions) can be daunting and impractical even for a small-sized problem. We introduced an efficient pruning strategy and demonstrated the computational efficiency and statistical power of the proposed method using both synthetic and real data.

READ FULL TEXT

page 8

page 22

06/26/2015

An Efficient Post-Selection Inference on High-Order Interaction Models

Finding statistically significant high-order interaction features in pre...
02/23/2021

Learning High-Order Interactions via Targeted Pattern Search

Logistic Regression (LR) is a widely used statistical method in empirica...
06/26/2015

Safe Feature Pruning for Sparse High-Order Interaction Models

Taking into account high-order interactions among covariates is valuable...
08/16/2016

A Shallow High-Order Parametric Approach to Data Visualization and Compression

Explicit high-order feature interactions efficiently capture essential s...
07/08/2022

Nonparametric Embeddings of Sparse High-Order Interaction Events

High-order interaction events are common in real-world applications. Lea...
02/15/2016

Selective Inference Approach for Statistically Sound Predictive Pattern Mining

Discovering statistically significant patterns from databases is an impo...
06/26/2017

Iterative Random Forests to detect predictive and stable high-order interactions

Genomics has revolutionized biology, enabling the interrogation of whole...