Quick Start

Under app/ folder is a example of a application using irec and mlflow, where different experiments can be run with easy using existing recommender systems.

Example

Check this example of a execution using the example application:

dataset=("Netflix 10k" "Good Books" "Yahoo Music 10k");\
models=(Random MostPopular UCB ThompsonSampling EGreedy);\
metrics=(Hits Precision Recall);\
eval_pol=("FixedInteraction");
metric_evaluator="Interaction";\

cd agents &&
python run_agent_best.py --agents "${models[@]}" --dataset_loaders "${dataset[@]}" --evaluation_policy "${eval_pol[@]}" &&

cd ../evaluation &&
python eval_agent_best.py --agents "${models[@]}" --dataset_loaders "${dataset[@]}" --evaluation_policy "${eval_pol[@]}" --metrics "${metrics[@]}" --metric_evaluator "${metric_eval[@]}" &&

python print_latex_table_results.py --agents "${models[@]}" --dataset_loaders "${dataset[@]}" --evaluation_policy "${eval_pol[@]}" --metric_evaluator "${metric_eval[@]}" --metrics "${metrics[@]}"

For more details, please take a look at our tutorials