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[DOCS] Removes outdated inference related limitation item. (#1104)
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docs/en/stack/ml/df-analytics/dfanalytics-limitations.asciidoc

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@@ -134,29 +134,3 @@ If a reduction in runtime is important to you, try strategies such as disabling
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feature importance, reducing the amount of training data (for example by
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decreasing the training percentage), setting <<hyperparameters,hyperparameter>>
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values, or only selecting fields that are relevant for analysis.
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[float]
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[[dfa-inference-multi-field]]
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=== Analytics training on multi-field values may affect {infer}
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{dfanalytics-jobs-cap} dynamically select the best field when multi-field
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values are included. For example, if a multi-field `foo` is included for training,
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the `foo.keyword` is actually used. This poses a complication for {infer} with
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the inference processor. Documents supplied to ingest pipelines are not mapped. Consequently,
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only the field `foo` is present. This means that a model trained with the field `foo.keyword`
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does not take the field `foo` into account.
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You can work around this limitation by using the `field_mappings` parameter in the inference processor.
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Example:
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```
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{
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"inference": {
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"model_id": "my_model_with_multi-fields",
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"field_mappings": {
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"foo": "foo.keyword"
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},
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"inference_config": { "regression": {} }
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}
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}
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```

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