5 papers
GitEvolve: Predicting the Evolution of GitHub Repositories
Honglu Zhou, Hareesh Ravi, Carlos M. Muniz +4
Software development is becoming increasingly open and collaborative with the advent of platforms such as GitHub. Given its crucial role, there is a need to better understand and m…
Heuristic Framework for Multi-Scale Testing of the Multi-Manifold Hypothesis
F. Patricia Medina, Linda Ness, Melanie Weber +1
When analyzing empirical data, we often find that global linear models overestimate the number of parameters required. In such cases, we may ask whether the data lies on or near a…
Inference of a Dyadic Measure and its Simplicial Geometry from Binary Feature Data and Application to Data Quality
Linda Ness
We propose a new method for representing data sets with a set of binary feature functions. We compute both the dyadic set structure determined by an order on the binary features to…
Product Formalisms for Measures on Spaces with Binary Tree Structures: Representation, Visualization, and Multiscale Noise
Devasis Bassu, Peter W. Jones, Linda Ness +1
In this paper we present a theoretical foundation for a representation of a data set as a measure in a very large hierarchically parametrized family of positive measures, whose par…
Multi-Scale Local Shape Analysis and Feature Selection in Machine Learning Applications
Paul Bendich, Ellen Gasparovic, John Harer +2
We introduce a method called multi-scale local shape analysis, or MLSA, for extracting features that describe the local structure of points within a dataset. The method uses both g…