LPmade: Link Prediction Made Easy
Abstract
LPmade is a complete cross-platform software solution for multi-core link prediction and related tasks and analysis. Its first principal contribution is a scalable network library supporting high-performance implementations of the most commonly employed unsupervised link prediction methods. Link prediction in longitudinal data requires a sophisticated and disciplined procedure for correct results and fair evaluation, so the second principle contribution of LPmade is a sophisticated GNU make architecture that completely automates link prediction, prediction evaluation, and network analysis. Finally, LPmade streamlines and automates the procedure for creating multivariate supervised link prediction models with a version of WEKA modified to operate effectively on extremely large data sets. With mere minutes of manual work, one may start with a raw stream of records representing a network and progress through hundreds of steps to generate plots, gigabytes or terabytes of output, and actionable or publishable results.
Cite
Text
Lichtenwalter and Chawla. "LPmade: Link Prediction Made Easy." Machine Learning Open Source Software, 2011.Markdown
[Lichtenwalter and Chawla. "LPmade: Link Prediction Made Easy." Machine Learning Open Source Software, 2011.](https://mlanthology.org/mloss/2011/lichtenwalter2011jmlr-lpmade/)BibTeX
@article{lichtenwalter2011jmlr-lpmade,
title = {{LPmade: Link Prediction Made Easy}},
author = {Lichtenwalter, Ryan N. and Chawla, Nitesh V.},
journal = {Machine Learning Open Source Software},
year = {2011},
pages = {2489-2492},
volume = {12},
url = {https://mlanthology.org/mloss/2011/lichtenwalter2011jmlr-lpmade/}
}