anchor.diff:  `estimated_operations`:::
   (integer)
   The estimated number of operations to use the trained model.
  +
  +`inference_config`:::
  +(object)
  +The default configuration for inference. This can be either a `regression`
  +or `classification` configuration. It must match the underlying
  +`definition.trained_model`'s `target_type`.
  ++
  +.Properties of `inference_config`
  +[%collapsible%open]
  +=====
  +`classification`::::
  +(object)
  +Classification configuration for inference.
  ++
  +.Properties of classification inference
  +[%collapsible%open]
  +======
  +`num_top_classes`:::
  +(integer)
  +include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=inference-config-classification-num-top-classes]
  +
  +`num_top_feature_importance_values`:::
  +(integer)
  +include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=inference-config-classification-num-top-feature-importance-values]
  +
  +`prediction_field_type`:::
  +(string)
  +include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=inference-config-classification-prediction-field-type]
  +
  +`results_field`:::
  +(string)
  +include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=inference-config-results-field]
  +
  +`top_classes_results_field`:::
  +(string)
  +include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=inference-config-classification-top-classes-results-field]
  +======
  +`regression`::::
  +(object)
  +Regression configuration for inference.
  ++
  +.Properties of regression inference
  +[%collapsible%open]
  +======
  +`num_top_feature_importance_values`:::
  +(integer)
  +include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=inference-config-regression-num-top-feature-importance-values]
  +
  +`results_field`:::
  +(string)
  +include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=inference-config-results-field]
  +======
  +=====
  +
  +`input`:::
  +(object)
  +The input field names for the model definition.+
  ++
  +.Properties of `input`
  +[%collapsible%open]
  +=====
  +`field_names`::::
  +(string)
  +An array of input field names for the model.
  +=====
   
   `license_level`:::
   (string)
  
positive.code: `version`:::
  (string)
  The {es} version number in which the trained model was created.
  ====
  
  
  
negative.code: +
  Any field map described in the inference configuration takes precedence.
  
  `description`:::
  (string)
  The free-text description of the trained model.
  
  `estimated_heap_memory_usage_bytes`:::
  (integer)
  The estimated heap usage in bytes to keep the trained model in memory.
  