Elliot: a Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
This tool addresses the problem of fragmented and non-reproducible evaluation for researchers in recommender systems, though it is incremental as it builds on existing evaluation practices.
The authors tackled the challenge of rigorous and reproducible experimental evaluation in recommender systems by developing Elliot, a comprehensive framework that processes a simple configuration file to run entire experimental pipelines, including data splitting, hyperparameter optimization, model selection, and statistical analysis, supporting 50 algorithms, 51 hyperparameter strategies, and 36 metrics.
Recommender Systems have shown to be an effective way to alleviate the over-choice problem and provide accurate and tailored recommendations. However, the impressive number of proposed recommendation algorithms, splitting strategies, evaluation protocols, metrics, and tasks, has made rigorous experimental evaluation particularly challenging. Puzzled and frustrated by the continuous recreation of appropriate evaluation benchmarks, experimental pipelines, hyperparameter optimization, and evaluation procedures, we have developed an exhaustive framework to address such needs. Elliot is a comprehensive recommendation framework that aims to run and reproduce an entire experimental pipeline by processing a simple configuration file. The framework loads, filters, and splits the data considering a vast set of strategies (13 splitting methods and 8 filtering approaches, from temporal training-test splitting to nested K-folds Cross-Validation). Elliot optimizes hyperparameters (51 strategies) for several recommendation algorithms (50), selects the best models, compares them with the baselines providing intra-model statistics, computes metrics (36) spanning from accuracy to beyond-accuracy, bias, and fairness, and conducts statistical analysis (Wilcoxon and Paired t-test). The aim is to provide the researchers with a tool to ease (and make them reproducible) all the experimental evaluation phases, from data reading to results collection. Elliot is available on GitHub (https://github.com/sisinflab/elliot).