GenRS 0.0.3

A State-Of-Art framework for Recommendation Systems algorithms

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:

• CFGAN
• IRGAN
• EASE
• VAE
• DAE

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