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@@ -4,18 +4,18 @@ tags:
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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-average-precision)"
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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 map
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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-average-precision)
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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