pyRecLab: A Software Library for Quick Prototyping of Recommender Systems
This provides an accessible tool for less experienced programmers to prototype recommender systems quickly, but it is incremental as it builds on existing libraries with a focus on Python usability.
The authors introduced pyRecLab, a C++/Python library for rapid prototyping of recommender systems, benchmarking it against LibRec with similar performance in error metrics (MAE and RMSE) and train/test times.
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.