Parameter settings for post-processing models

(Default values are in ~/recommendation/Post-processing.yaml)

The benchmark provides several arguments for describing:

• Basic setting of the parameters

See below for the details:

Post-processing required parameters

Model set ups

• ranking_store_path (str) : The log path of the in-processing models, which stores the ranking scores for re-ranking

• model (str) : The post-processing model name.

Log set ups

• log_name (str) : The running log name, which will create a new dictionary ~recommendationloglog_nameand store the test results and all parameters into it.

Evaluation set ups

• fairness_metrics (list) : The fairness metrics you want to record

• fairness_type (str) : The fairness computational methods, choosed among [“Exposure”, “Utility”]. Exposure means computes fairness on the item exposure, Uility means computes fairness on the ranking scores.

For other evaluation settings, please reference to parameters in evaluation.rst