A Generative learning-based Framework for Recommendation System algorithms
Project description
GenRS
A generative learning-based Framework for Recommendation Systems algorithms
Software requirements:
- Python 3.6 or higher
- Tensorflow 1.15 GPU
- Numpy 1.17
- Scipy 1.3
- Pandas 0.25
- Bottleneck 1.3
Algorithms list available:
TO DO:
- Check which dataset you want to use from here
- Download and extract the preferred into Dataset folder
Set the framework configuration in Data/cfg.JSON
- Check if path contains the path to your chosen dataset file
- Check separator (sep) used in selected dataset and update if necessary
- Check algos you want to compute respecting the list of string lowercase format as predefined
- Define the number of users to use as validation and test set through heldout_us_val and heldout_us_test param
- Check metrics you want to compute from: ["precision@k", "recall@k", "ndcg@k", "ap@k", "auc"]
Set the algorithms configuration in Data/alg_cfg.JSON where alg are the name previously set in algos
Run Main/main.py
Results will be into console.log.txt file
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