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@ -191,10 +191,10 @@ belongs.
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positive.
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`class_name`::::
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(Required, string) Name of the only class that will be treated as
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positive during AUC ROC calculation. Other classes will be treated as
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negative ("one-vs-all" strategy). All the evaluated documents must have `class_name`
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in the list of their top classes.
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(Required, string) Name of the only class that is treated as positive
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during AUC ROC calculation. Other classes are treated as negative
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("one-vs-all" strategy). All the evaluated documents must have
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`class_name` in the list of their top classes.
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`include_curve`::::
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(Optional, boolean) Whether or not the curve should be returned in
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@ -496,3 +496,46 @@ predictions associated with the class.
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<5> The number of cats in the dataset that are incorrectly classified as dogs.
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<6> The number of documents that are classified as a class that is not listed as
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a `predicted_class`.
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[source,console]
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--------------------------------------------------
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POST _ml/data_frame/_evaluate
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{
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"index": "animal_classification",
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"evaluation": {
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"classification": { <1>
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"actual_field": "animal_class", <2>
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"metrics": {
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"auc_roc" : { <3>
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"class_name": "dog" <4>
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}
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}
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}
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}
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}
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--------------------------------------------------
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// TEST[skip:TBD]
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<1> The evaluation type.
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<2> The field that contains the ground truth value for the actual animal
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classification. This is required in order to evaluate results.
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<3> Specifies the metric for the evaluation.
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<4> Specifies the class name that is treated as positive during the evaluation,
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all the other classes are treated as negative.
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The API returns the following result:
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[source,console-result]
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--------------------------------------------------
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{
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"classification" : {
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"auc_roc" : {
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"score" : 0.8941788639536681
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}
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}
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}
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--------------------------------------------------
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// TEST[skip:TBD]
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