Super Partition: fast, flexible, and interpretable large-scale data reduction in R.

ABSTRACT:

Motivation

As data sets increase in size and complexity with advancing technology, flexible and interpretable data reduction methods that quantify information preservation become increasingly important.

Results

Super Partition is a large-scale approximation of the original Partition data reduction algorithm that allows the user to flexibly specify the minimum amount of information captured for each input feature. In an initial step, Genie, a fast, hierarchical clustering algorithm, forms a super-partition, thereby increasing the computational tractability by allowing Partition to be applied to the subsets. Applications to high dimensional data sets show scalability to hundreds of thousands of features with reasonable computation times.

Availability and implementation

SUBMITTER: Queen KJ 

PROVIDER: S-EPMC11781262 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature