Get trained model configuration info Added in 7.10.0
Query parameters
-
allow_no_match boolean
Specifies what to do when the request:
- Contains wildcard expressions and there are no models that match.
- Contains the _all string or no identifiers and there are no matches.
- Contains wildcard expressions and there are only partial matches.
If true, it returns an empty array when there are no matches and the subset of results when there are partial matches.
-
decompress_definition boolean
Specifies whether the included model definition should be returned as a JSON map (true) or in a custom compressed format (false).
-
exclude_generated boolean
Indicates if certain fields should be removed from the configuration on retrieval. This allows the configuration to be in an acceptable format to be retrieved and then added to another cluster.
-
from number
Skips the specified number of models.
-
include string
A comma delimited string of optional fields to include in the response body.
Values are
definition
,feature_importance_baseline
,hyperparameters
,total_feature_importance
, ordefinition_status
. -
size number
Specifies the maximum number of models to obtain.
curl \
-X GET http://api.example.com/_ml/trained_models
{
"count": 42.0,
"trained_model_configs": [
{
"model_id": "string",
"model_type": "tree_ensemble",
"tags": [
"string"
],
"version": "string",
"compressed_definition": "string",
"created_by": "string",
"": 42.0,
"default_field_map": {
"additionalProperty1": "string",
"additionalProperty2": "string"
},
"description": "string",
"estimated_heap_memory_usage_bytes": 42.0,
"estimated_operations": 42.0,
"fully_defined": true,
"inference_config": {
"regression": {
"results_field": "string",
"num_top_feature_importance_values": 42.0
},
"classification": {
"num_top_classes": 42.0,
"num_top_feature_importance_values": 42.0,
"prediction_field_type": "string",
"results_field": "string",
"top_classes_results_field": "string"
},
"text_classification": {
"num_top_classes": 42.0,
"tokenization": {
"bert": {},
"mpnet": {},
"roberta": {}
},
"results_field": "string",
"classification_labels": [
"string"
]
},
"zero_shot_classification": {
"tokenization": {
"bert": {},
"mpnet": {},
"roberta": {}
},
"hypothesis_template": "string",
"classification_labels": [
"string"
],
"results_field": "string",
"multi_label": true,
"labels": [
"string"
]
},
"fill_mask": {
"mask_token": "string",
"num_top_classes": 42.0,
"tokenization": {
"bert": {},
"mpnet": {},
"roberta": {}
},
"results_field": "string"
},
"ner": {
"tokenization": {
"bert": {},
"mpnet": {},
"roberta": {}
},
"results_field": "string",
"classification_labels": [
"string"
],
"vocabulary": {
"index": "string"
}
},
"pass_through": {
"tokenization": {
"bert": {},
"mpnet": {},
"roberta": {}
},
"results_field": "string",
"vocabulary": {
"index": "string"
}
},
"text_embedding": {
"embedding_size": 42.0,
"tokenization": {
"bert": {},
"mpnet": {},
"roberta": {}
},
"results_field": "string"
},
"text_expansion": {
"tokenization": {
"bert": {},
"mpnet": {},
"roberta": {}
},
"results_field": "string"
},
"question_answering": {
"num_top_classes": 42.0,
"tokenization": {
"bert": {},
"mpnet": {},
"roberta": {}
},
"results_field": "string",
"max_answer_length": 42.0
}
},
"input": {
"field_names": [
"string"
]
},
"license_level": "string",
"metadata": {
"model_aliases": [
"string"
],
"feature_importance_baseline": {
"additionalProperty1": "string",
"additionalProperty2": "string"
},
"hyperparameters": [
{
"absolute_importance": 42.0,
"name": "string",
"relative_importance": 42.0,
"supplied": true,
"value": 42.0
}
],
"total_feature_importance": [
{
"feature_name": "string",
"importance": [
{}
],
"classes": [
{}
]
}
]
},
"location": {
"index": {
"name": "string"
}
},
"prefix_strings": {
"ingest": "string",
"search": "string"
}
}
]
}