friends.test: Rank-Based Feature Selection for Interaction Matrices
Published:Dec 31, 2025 13:03
•1 min read
•ArXiv
Analysis
This paper introduces a novel method, friends.test, for feature selection in interaction matrices, a common problem in various scientific domains. The method's key strength lies in its rank-based approach, which makes it robust to data heterogeneity and allows for integration of data from different sources. The use of model fitting to identify specific interactions is also a notable aspect. The availability of an R implementation is a practical advantage.
Key Takeaways
- •friends.test is a rank-based method for feature selection in interaction matrices.
- •The method is designed to handle heterogeneous data from diverse sources.
- •It uses model fitting to identify specific interactions.
- •An R implementation is available for practical use.
Reference
“friends.test identifies specificity by detecting structural breaks in entity interactions.”