pyRecLab: A Software Library for Quick Prototyping of Recommender Systems
This paper introduces pyRecLab, a software library written in C++ with Python bindings which allows to quickly train, test and develop recommender systems. Although there are several software libraries for this purpose, only a few let developers to get quickly started with the most traditional methods, permitting them to try different parameters and approach several tasks without a significant loss of performance. Among the few libraries that have all these features, they are available in languages such as Java, Scala or C#, what is a disadvantage for less experienced programmers more used to the popular Python programming language. In this article we introduce details of pyRecLab, showing as well performance analysis in terms of error metrics (MAE and RMSE) and train/test time. We benchmark it against the popular Java-based library LibRec, showing similar results. We expect programmers with little experience and people interested in quickly prototyping recommender systems to be benefited from pyRecLab.
Code (1)
Tasks
Recommendation SystemsSimilar Papers 제목 키워드 기반
SCENIC: A JAX Library for Computer Vision Research and Beyond
Scenic is an open-source JAX library with a focus on Transformer-based models for computer vision research and beyond. The goal of this toolkit is to facilitate rapid experimentation, prototyping, and research of new vis…
GPUlearn2learn: A Library for Meta-Learning Research
Meta-learning researchers face two fundamental issues in their empirical work: prototyping and reproducibility. Researchers are prone to make mistakes when prototyping new algorithms and tasks because modern meta-learnin…
Few-Shot LearningMeta-LearningMeta Reinforcement LearningRGRecSys: A Toolkit for Robustness Evaluation of Recommender Systems
Robust machine learning is an increasingly important topic that focuses on developing models resilient to various forms of imperfect data. Due to the pervasiveness of recommender systems in online technologies, researche…
Recommendation SystemsPrototyping with SDR: a quick way to play with next-gen communications systems
In this paper we present our approach regarding the implementation of new wireless radio receiver exploiting filterbank techniques, using a software-development driven approach. Since most of the common radio communicati…
Grad DFT: a software library for machine learning enhanced density functional theory
Density functional theory (DFT) stands as a cornerstone method in computational quantum chemistry and materials science due to its remarkable versatility and scalability. Yet, it suffers from limitations in accuracy, par…
Benchmarking