Charles Englebert
2333223c1c
* ✨(backend) add evaluate-search-engine command I want to automize the search evaluation. This new command computes performance metrics. * ✨(backend) improve evaluation I add more data to my evaluations. * 📝(backend) add changelog add changelog and various fixes. * ✨(backend) add more data I add more data to evaluation * ✨(backend) add index management flags I add --keep-index and --force-reindex flags * ♻️(backend) remove dependences from test/utils I remove dependences from test/utils * 📝(backend) documenting I add documentation of the command * ♻️(backend) break unique documents file into text files I change the data structure of the documents * 🚨(backend) fix things things were broken but here I fix them * ♻️(backend) evaluation app I move the command to an evaluation app * 🧪(backend) add tests I add test on the command * 🚨(backend) fix thing thinghs must be fixed.
1.0 KiB
1.0 KiB
Search Engine Evaluation Command
Overview
this Django command atomizes the evaluation of the search engine by computing 4 metrics: Average Discounted Cumulative Gain, Precision, Recall and F1 score.
Usage
python manage.py evaluate_search_engine <dataset_name> [options]
Required Arguments
dataset_name: Name of the evaluation dataset to use. Datasets are located inevaluation/management/commands/data/evaluation/
Optional Arguments
--min_score: Minimum score threshold; hits below this score are ignored--keep-index: Preserve the evaluation index after completion--force-reindex: Drop and recreate the index even if it exists
Examples
# Basic evaluation with default settings
python manage.py evaluate_search_engine my_dataset
# Evaluation with minimum score threshold
python manage.py evaluate_search_engine my_dataset --min_score 0.5
# Force reindexing and clean up afterward
python manage.py evaluate_search_engine my_dataset --force-reindex True --keep-index False