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README.md
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- evaluate
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- metric
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description: "This is the mean reciprocal rank (mrr) metric for retrieval systems.
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It is the average of the precision scores computer after each relevant document is got. You can refer to [here](https://amenra.github.io/ranx/metrics/#mean-
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sdk: gradio
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sdk_version: 3.19.1
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app_file: app.py
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pinned: false
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---
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# Metric Card for
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## Metric Description
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This is the mean average precision (map) metric for retrieval systems.
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It is the average of the precision scores computer after each relevant document is got. You can refer to [here](https://amenra.github.io/ranx/metrics/#mean-
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## How to Use
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```python
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- evaluate
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- metric
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description: "This is the mean reciprocal rank (mrr) metric for retrieval systems.
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+
It is the average of the precision scores computer after each relevant document is got. You can refer to [here](https://amenra.github.io/ranx/metrics/#mean-reciprocal-rank)"
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sdk: gradio
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sdk_version: 3.19.1
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app_file: app.py
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pinned: false
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---
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# Metric Card for mrr
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## Metric Description
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This is the mean average precision (map) metric for retrieval systems.
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It is the average of the precision scores computer after each relevant document is got. You can refer to [here](https://amenra.github.io/ranx/metrics/#mean-reciprocal-rank)
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## How to Use
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```python
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