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A Framework for validating two ranked lists using ndcg, kendall's tau, rbo, recall, mrr

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akashkdubey/ranking_validation

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Ranking Validation

This python package generates two ranking validation reports, one is a query level report that would contain information on the metrics provided as input and the overall metrics report which is a summarised version of query level report.

Introduction

The packages essentially compares two ranked lists at its core but scales it to a dataframe and automates the process of comparing two ranked lists for different queries for different set of metrics and at different cutoffs.

Usage

Installation using pip

pip install rank-validation

Getting the validation report

from rank_validation.validation_generator import get_metrics_report
query_report, overall_report = get_metrics_report(df, truth item column, truth score column, pred item col, metrics, cutoff)

Current version supports the following metrics:

- ndcg
- kendall_tau
- recall
- rbo

Note : rbo might run into errors if : len(set(ground_truth_items)) != len(set(predicted_items)), so if rbo gives an error, try generating the report with other metrics available.

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A Framework for validating two ranked lists using ndcg, kendall's tau, rbo, recall, mrr

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