[Docs] Add rank_eval size parameter k (#29218)
The rank_eval documentation was missing an explanation of the parameter `k` that controls the number of top hits that are used in the ranking evaluation. Closes #29205
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[[search-rank-eval]]
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== Ranking Evaluation API
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experimental[The ranking evaluation API is experimental and may be changed or removed completely in a future release,
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as well as change in non-backwards compatible ways on minor versions updates. Elastic will take a best effort
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approach to fix any issues, but experimental features are not subject to the support SLA of official GA features.]
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The ranking evaluation API allows to evaluate the quality of ranked search
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results over a set of typical search queries. Given this set of queries and a
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list or manually rated documents, the `_rank_eval` endpoint calculates and
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returns typical information retrieval metrics like _mean reciprocal rank_,
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_precision_ or _discounted cumulative gain_.
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experimental[The ranking evaluation API is new and may change in non-backwards compatible ways in the future, even on minor versions updates.]
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[float]
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=== Overview
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@ -41,7 +43,7 @@ GET /my_index/_rank_eval
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{
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"requests": [ ... ], <1>
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"metric": { <2>
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"reciprocal_rank": { ... } <3>
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"mean_reciprocal_rank": { ... } <3>
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}
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}
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------------------------------
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@ -158,6 +160,7 @@ GET /twitter/_rank_eval
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}],
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"metric": {
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"precision": {
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"k" : 20,
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"relevant_rating_threshold": 1,
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"ignore_unlabeled": false
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}
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@ -172,7 +175,9 @@ The `precision` metric takes the following optional parameters
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[cols="<,<",options="header",]
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|=======================================================================
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|Parameter |Description
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|`relevant_rating_threshold` |Sets the rating threshold above which documents are considered to be
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|`k` |sets the maximum number of documents retrieved per query. This value will act in place of the usual `size` parameter
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in the query. Defaults to 10.
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|`relevant_rating_threshold` |sets the rating threshold above which documents are considered to be
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"relevant". Defaults to `1`.
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|`ignore_unlabeled` |controls how unlabeled documents in the search results are counted.
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If set to 'true', unlabeled documents are ignored and neither count as relevant or irrelevant. Set to 'false' (the default), they are treated as irrelevant.
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@ -198,6 +203,7 @@ GET /twitter/_rank_eval
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}],
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"metric": {
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"mean_reciprocal_rank": {
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"k" : 20,
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"relevant_rating_threshold" : 1
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}
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}
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@ -211,6 +217,8 @@ The `mean_reciprocal_rank` metric takes the following optional parameters
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[cols="<,<",options="header",]
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|=======================================================================
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|Parameter |Description
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|`k` |sets the maximum number of documents retrieved per query. This value will act in place of the usual `size` parameter
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in the query. Defaults to 10.
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|`relevant_rating_threshold` |Sets the rating threshold above which documents are considered to be
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"relevant". Defaults to `1`.
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|=======================================================================
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@ -234,6 +242,7 @@ GET /twitter/_rank_eval
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}],
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"metric": {
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"dcg": {
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"k" : 20,
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"normalize": false
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}
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}
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@ -247,6 +256,8 @@ The `dcg` metric takes the following optional parameters:
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[cols="<,<",options="header",]
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|=======================================================================
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|Parameter |Description
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|`k` |sets the maximum number of documents retrieved per query. This value will act in place of the usual `size` parameter
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in the query. Defaults to 10.
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|`normalize` | If set to `true`, this metric will calculate the https://en.wikipedia.org/wiki/Discounted_cumulative_gain#Normalized_DCG[Normalized DCG].
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|=======================================================================
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