Preview features used by data frame analytics | Elasticsearch API documentation (8x-unreleased)

Preview features used by data frame analytics Generally available; Added in 7.13.0

POST /_ml/data_frame/analytics/{id}/_preview

Preview the extracted features used by a data frame analytics config. ##Required authorization

Cluster privileges: monitor_ml

Path parameters

id string Required

Identifier for the data frame analytics job.

application/json

Body

config object
Hide config attributes Show config attributes object
- source object Required
  Hide source attributes Show source attributes object
  
  index string | array[string] Required
  
  query object
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  External documentation
  
  Hide query attributes Show query attributes object
  
  bool object
  
  Hide bool attributes Show bool attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  filter object | array[object]
  
  The clause (query) must appear in matching documents. However, unlike must, the score of the query will be ignored.
  
  One of:
  QueryContainer object array-2 array[object]
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  minimum_should_match number | string
  
  The minimum number of terms that should match as integer, percentage or range
  
  One of:
  MinimumShouldMatch number MinimumShouldMatch string
  
  must object | array[object]
  
  The clause (query) must appear in matching documents and will contribute to the score.
  
  One of:
  QueryContainer object array-2 array[object]
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  must_not object | array[object]
  
  The clause (query) must not appear in the matching documents. Because scoring is ignored, a score of 0 is returned for all documents.
  
  One of:
  QueryContainer object array-2 array[object]
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  should object | array[object]
  
  The clause (query) should appear in the matching document.
  
  One of:
  QueryContainer object array-2 array[object]
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  boosting object
  
  Hide boosting attributes Show boosting attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  negative_boost number Required
  
  Floating point number between 0 and 1.0 used to decrease the relevance scores of documents matching the negative query.
  
  negative object Required
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  positive object Required
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  common object Deprecated
  
  combined_fields object
  
  Hide combined_fields attributes Show combined_fields attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  fields array[string] Required
  
  List of fields to search. Field wildcard patterns are allowed. Only text fields are supported, and they must all have the same search analyzer.
  
  query string Required
  
  Text to search for in the provided fields. The combined_fields query analyzes the provided text before performing a search.
  
  auto_generate_synonyms_phrase_query boolean
  
  If true, match phrase queries are automatically created for multi-term synonyms.
  
  operator string
  
  Values are or or and.
  
  minimum_should_match number | string
  
  The minimum number of terms that should match as integer, percentage or range
  
  One of:
  MinimumShouldMatch number MinimumShouldMatch string
  
  zero_terms_query string
  
  Values are none or all.
  
  constant_score object
  
  Hide constant_score attributes Show constant_score attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  filter object Required
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  dis_max object
  
  Hide dis_max attributes Show dis_max attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  queries array[object] Required
  
  One or more query clauses. Returned documents must match one or more of these queries. If a document matches multiple queries, Elasticsearch uses the highest relevance score.
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  tie_breaker number
  
  Floating point number between 0 and 1.0 used to increase the relevance scores of documents matching multiple query clauses.
  
  distance_feature object
  
  One of:
  UntypedDistanceFeatureQuery object GeoDistanceFeatureQuery object DateDistanceFeatureQuery object
  
  exists object
  
  Hide exists attributes Show exists attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  field string Required
  
  Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.
  
  function_score object
  
  Hide function_score attributes Show function_score attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  boost_mode string
  
  Values are multiply, replace, sum, avg, max, or min.
  
  functions array[object]
  
  One or more functions that compute a new score for each document returned by the query.
  
  max_boost number
  
  Restricts the new score to not exceed the provided limit.
  
  min_score number
  
  Excludes documents that do not meet the provided score threshold.
  
  query object
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  score_mode string
  
  Values are multiply, sum, avg, first, max, or min.
  
  fuzzy object
  
  Returns documents that contain terms similar to the search term, as measured by a Levenshtein edit distance.
  
  External documentation
  
  geo_bounding_box object
  
  Hide geo_bounding_box attributes Show geo_bounding_box attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  type string
  
  Values are memory or indexed.
  
  validation_method string
  
  Values are coerce, ignore_malformed, or strict.
  
  ignore_unmapped boolean
  
  Set to true to ignore an unmapped field and not match any documents for this query. Set to false to throw an exception if the field is not mapped.
  
  geo_distance object
  
  Hide geo_distance attributes Show geo_distance attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  distance string Required
  
  distance_type string
  
  Values are arc or plane.
  
  validation_method string
  
  Values are coerce, ignore_malformed, or strict.
  
  ignore_unmapped boolean
  
  Set to true to ignore an unmapped field and not match any documents for this query. Set to false to throw an exception if the field is not mapped.
  
  geo_grid object
  
  Matches geo_point and geo_shape values that intersect a grid cell from a GeoGrid aggregation.
  
  geo_polygon object
  
  Hide geo_polygon attributes Show geo_polygon attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  validation_method string
  
  Values are coerce, ignore_malformed, or strict.
  
  ignore_unmapped boolean
  
  geo_shape object
  
  Hide geo_shape attributes Show geo_shape attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  ignore_unmapped boolean
  
  Set to true to ignore an unmapped field and not match any documents for this query. Set to false to throw an exception if the field is not mapped.
  
  has_child object
  
  Hide has_child attributes Show has_child attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  ignore_unmapped boolean
  
  Indicates whether to ignore an unmapped type and not return any documents instead of an error.
  
  inner_hits object
  
  Hide inner_hits attributes Show inner_hits attributes object
  
  name string
  
  size number
  
  The maximum number of hits to return per inner_hits.
  
  from number
  
  Inner hit starting document offset.
  
  collapse object
  
  docvalue_fields array[object]
  
  explain boolean
  
  ignore_unmapped boolean
  
  script_fields object
  
  seq_no_primary_term boolean
  
  fields array[string]
  
  Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.
  
  sort
  
  _source
  
  stored_fields string | array[string]
  
  track_scores boolean
  
  version boolean
  
  max_children number
  
  Maximum number of child documents that match the query allowed for a returned parent document. If the parent document exceeds this limit, it is excluded from the search results.
  
  min_children number
  
  Minimum number of child documents that match the query required to match the query for a returned parent document. If the parent document does not meet this limit, it is excluded from the search results.
  
  query object Required
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  score_mode string
  
  Values are none, avg, sum, max, or min.
  
  type string Required
  
  has_parent object
  
  Hide has_parent attributes Show has_parent attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  ignore_unmapped boolean
  
  Indicates whether to ignore an unmapped parent_type and not return any documents instead of an error. You can use this parameter to query multiple indices that may not contain the parent_type.
  
  inner_hits object
  
  Hide inner_hits attributes Show inner_hits attributes object
  
  name string
  
  size number
  
  The maximum number of hits to return per inner_hits.
  
  from number
  
  Inner hit starting document offset.
  
  collapse object
  
  docvalue_fields array[object]
  
  explain boolean
  
  ignore_unmapped boolean
  
  script_fields object
  
  seq_no_primary_term boolean
  
  fields array[string]
  
  Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.
  
  sort
  
  _source
  
  stored_fields string | array[string]
  
  track_scores boolean
  
  version boolean
  
  parent_type string Required
  
  query object Required
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  score boolean
  
  Indicates whether the relevance score of a matching parent document is aggregated into its child documents.
  
  ids object
  
  Hide ids attributes Show ids attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  values string | array[string]
  
  One of:
  Id string Ids array[string]
  
  intervals object
  
  Returns documents based on the order and proximity of matching terms.
  
  External documentation
  
  knn object
  
  Hide knn attributes Show knn attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  field string Required
  
  Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.
  
  query_vector array[number]
  
  query_vector_builder object
  
  Hide query_vector_builder attribute Show query_vector_builder attribute object
  
  text_embedding object
  
  num_candidates number
  
  The number of nearest neighbor candidates to consider per shard
  
  k number
  
  The final number of nearest neighbors to return as top hits
  
  filter object | array[object]
  
  Filters for the kNN search query
  
  One of:
  QueryContainer object array-2 array[object]
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  similarity number
  
  The minimum similarity for a vector to be considered a match
  
  rescore_vector object
  
  Hide rescore_vector attribute Show rescore_vector attribute object
  
  oversample number Required
  
  Applies the specified oversample factor to k on the approximate kNN search
  
  match object
  
  Returns documents that match a provided text, number, date or boolean value. The provided text is analyzed before matching.
  
  External documentation
  
  match_all object
  
  Hide match_all attributes Show match_all attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  match_bool_prefix object
  
  Analyzes its input and constructs a bool query from the terms. Each term except the last is used in a term query. The last term is used in a prefix query.
  
  External documentation
  
  match_none object
  
  Hide match_none attributes Show match_none attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  match_phrase object
  
  Analyzes the text and creates a phrase query out of the analyzed text.
  
  External documentation
  
  match_phrase_prefix object
  
  Returns documents that contain the words of a provided text, in the same order as provided. The last term of the provided text is treated as a prefix, matching any words that begin with that term.
  
  External documentation
  
  more_like_this object
  
  Hide more_like_this attributes Show more_like_this attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  analyzer string
  
  The analyzer that is used to analyze the free form text. Defaults to the analyzer associated with the first field in fields.
  
  External documentation
  
  boost_terms number
  
  Each term in the formed query could be further boosted by their tf-idf score. This sets the boost factor to use when using this feature. Defaults to deactivated (0).
  
  fail_on_unsupported_field boolean
  
  Controls whether the query should fail (throw an exception) if any of the specified fields are not of the supported types (text or keyword).
  
  fields array[string]
  
  A list of fields to fetch and analyze the text from. Defaults to the index.query.default_field index setting, which has a default value of *.
  
  include boolean
  
  Specifies whether the input documents should also be included in the search results returned.
  
  like array[string | object] Required
  
  max_doc_freq number
  
  The maximum document frequency above which the terms are ignored from the input document.
  
  max_query_terms number
  
  The maximum number of query terms that can be selected.
  
  max_word_length number
  
  The maximum word length above which the terms are ignored. Defaults to unbounded (0).
  
  min_doc_freq number
  
  The minimum document frequency below which the terms are ignored from the input document.
  
  minimum_should_match number | string
  
  The minimum number of terms that should match as integer, percentage or range
  
  One of:
  MinimumShouldMatch number MinimumShouldMatch string
  
  min_term_freq number
  
  The minimum term frequency below which the terms are ignored from the input document.
  
  min_word_length number
  
  The minimum word length below which the terms are ignored.
  
  routing string
  
  stop_words string | array[string]
  
  Language value, such as arabic or thai. Defaults to english. Each language value corresponds to a predefined list of stop words in Lucene. See Stop words by language for supported language values and their stop words. Also accepts an array of stop words.
  
  One of:
  StopWordLanguage string StopWords array[string]
  
  Values are _arabic_, _armenian_, _basque_, _bengali_, _brazilian_, _bulgarian_, _catalan_, _cjk_, _czech_, _danish_, _dutch_, _english_, _estonian_, _finnish_, _french_, _galician_, _german_, _greek_, _hindi_, _hungarian_, _indonesian_, _irish_, _italian_, _latvian_, _lithuanian_, _norwegian_, _persian_, _portuguese_, _romanian_, _russian_, _serbian_, _sorani_, _spanish_, _swedish_, _thai_, _turkish_, or _none_.
  
  unlike array[string | object]
  
  version number
  
  version_type string
  
  Values are internal, external, external_gte, or force.
  
  multi_match object
  
  Hide multi_match attributes Show multi_match attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  analyzer string
  
  Analyzer used to convert the text in the query value into tokens.
  
  auto_generate_synonyms_phrase_query boolean
  
  If true, match phrase queries are automatically created for multi-term synonyms.
  
  cutoff_frequency number Deprecated
  
  fields string | array[string]
  
  fuzziness string | number
  
  One of:
  Fuzziness string Fuzziness number
  
  fuzzy_rewrite string
  
  fuzzy_transpositions boolean
  
  If true, edits for fuzzy matching include transpositions of two adjacent characters (for example, ab to ba). Can be applied to the term subqueries constructed for all terms but the final term.
  
  lenient boolean
  
  If true, format-based errors, such as providing a text query value for a numeric field, are ignored.
  
  max_expansions number
  
  Maximum number of terms to which the query will expand.
  
  minimum_should_match number | string
  
  The minimum number of terms that should match as integer, percentage or range
  
  One of:
  MinimumShouldMatch number MinimumShouldMatch string
  
  operator string
  
  Values are and, AND, or, or OR.
  
  prefix_length number
  
  Number of beginning characters left unchanged for fuzzy matching.
  
  query string Required
  
  Text, number, boolean value or date you wish to find in the provided field.
  
  slop number
  
  Maximum number of positions allowed between matching tokens.
  
  tie_breaker number
  
  Determines how scores for each per-term blended query and scores across groups are combined.
  
  type string
  
  Values are best_fields, most_fields, cross_fields, phrase, phrase_prefix, or bool_prefix.
  
  zero_terms_query string
  
  Values are all or none.
  
  nested object
  
  Hide nested attributes Show nested attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  ignore_unmapped boolean
  
  Indicates whether to ignore an unmapped path and not return any documents instead of an error.
  
  inner_hits object
  
  Hide inner_hits attributes Show inner_hits attributes object
  
  name string
  
  size number
  
  The maximum number of hits to return per inner_hits.
  
  from number
  
  Inner hit starting document offset.
  
  collapse object
  
  docvalue_fields array[object]
  
  explain boolean
  
  ignore_unmapped boolean
  
  script_fields object
  
  seq_no_primary_term boolean
  
  fields array[string]
  
  Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.
  
  sort
  
  _source
  
  stored_fields string | array[string]
  
  track_scores boolean
  
  version boolean
  
  path string Required
  
  Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.
  
  query object Required
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  score_mode string
  
  Values are none, avg, sum, max, or min.
  
  parent_id object
  
  Hide parent_id attributes Show parent_id attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  id string
  
  ignore_unmapped boolean
  
  Indicates whether to ignore an unmapped type and not return any documents instead of an error.
  
  type string
  
  percolate object
  
  Hide percolate attributes Show percolate attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  document object
  
  The source of the document being percolated.
  
  documents array[object]
  
  An array of sources of the documents being percolated.
  
  field string Required
  
  Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.
  
  id string
  
  index string
  
  name string
  
  The suffix used for the _percolator_document_slot field when multiple percolate queries are specified.
  
  preference string
  
  Preference used to fetch document to percolate.
  
  routing string
  
  version number
  
  pinned object
  
  Hide pinned attributes Show pinned attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  organic object Required
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  ids array[string]
  
  Document IDs listed in the order they are to appear in results. Required if docs is not specified.
  
  docs array[object]
  
  Documents listed in the order they are to appear in results. Required if ids is not specified.
  
  prefix object
  
  Returns documents that contain a specific prefix in a provided field.
  
  External documentation
  
  query_string object
  
  Hide query_string attributes Show query_string attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  allow_leading_wildcard boolean
  
  If true, the wildcard characters * and ? are allowed as the first character of the query string.
  
  analyzer string
  
  Analyzer used to convert text in the query string into tokens.
  
  analyze_wildcard boolean
  
  If true, the query attempts to analyze wildcard terms in the query string.
  
  auto_generate_synonyms_phrase_query boolean
  
  If true, match phrase queries are automatically created for multi-term synonyms.
  
  default_field string
  
  Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.
  
  default_operator string
  
  Values are and, AND, or, or OR.
  
  enable_position_increments boolean
  
  If true, enable position increments in queries constructed from a query_string search.
  
  escape boolean
  
  fields array[string]
  
  Array of fields to search. Supports wildcards (*).
  
  fuzziness string | number
  
  One of:
  Fuzziness string Fuzziness number
  
  fuzzy_max_expansions number
  
  Maximum number of terms to which the query expands for fuzzy matching.
  
  fuzzy_prefix_length number
  
  Number of beginning characters left unchanged for fuzzy matching.
  
  fuzzy_rewrite string
  
  fuzzy_transpositions boolean
  
  If true, edits for fuzzy matching include transpositions of two adjacent characters (for example, ab to ba).
  
  lenient boolean
  
  If true, format-based errors, such as providing a text value for a numeric field, are ignored.
  
  max_determinized_states number
  
  Maximum number of automaton states required for the query.
  
  minimum_should_match number | string
  
  The minimum number of terms that should match as integer, percentage or range
  
  One of:
  MinimumShouldMatch number MinimumShouldMatch string
  
  phrase_slop number
  
  Maximum number of positions allowed between matching tokens for phrases.
  
  query string Required
  
  Query string you wish to parse and use for search.
  
  quote_analyzer string
  
  Analyzer used to convert quoted text in the query string into tokens. For quoted text, this parameter overrides the analyzer specified in the analyzer parameter.
  
  quote_field_suffix string
  
  Suffix appended to quoted text in the query string. You can use this suffix to use a different analysis method for exact matches.
  
  rewrite string
  
  tie_breaker number
  
  How to combine the queries generated from the individual search terms in the resulting dis_max query.
  
  time_zone string
  
  type string
  
  Values are best_fields, most_fields, cross_fields, phrase, phrase_prefix, or bool_prefix.
  
  range object
  
  Returns documents that contain terms within a provided range.
  
  External documentation
  
  rank_feature object
  
  Hide rank_feature attributes Show rank_feature attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  field string Required
  
  Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.
  
  saturation object
  
  log object
  
  linear object
  
  sigmoid object
  
  regexp object
  
  Returns documents that contain terms matching a regular expression.
  
  External documentation
  
  rule object
  
  Hide rule attributes Show rule attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  organic object Required
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  ruleset_ids string | array[string]
  
  One of:
  Id string array-2 array[string]
  
  ruleset_id string
  
  match_criteria object Required
  
  script object
  
  Hide script attributes Show script attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  script object Required
  
  Hide script attributes Show script attributes object
  
  source
  
  id string
  
  params object
  
  Specifies any named parameters that are passed into the script as variables. Use parameters instead of hard-coded values to decrease compile time.
  
  lang
  
  options object
  
  script_score object
  
  Hide script_score attributes Show script_score attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  min_score number
  
  Documents with a score lower than this floating point number are excluded from the search results.
  
  query object Required
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  script object Required
  
  Hide script attributes Show script attributes object
  
  source
  
  id string
  
  params object
  
  Specifies any named parameters that are passed into the script as variables. Use parameters instead of hard-coded values to decrease compile time.
  
  lang
  
  options object
  
  semantic object
  
  Hide semantic attributes Show semantic attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  field string Required
  
  The field to query, which must be a semantic_text field type
  
  query string Required
  
  The query text
  
  shape object
  
  Hide shape attributes Show shape attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  ignore_unmapped boolean
  
  When set to true the query ignores an unmapped field and will not match any documents.
  
  simple_query_string object
  
  Hide simple_query_string attributes Show simple_query_string attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  analyzer string
  
  Analyzer used to convert text in the query string into tokens.
  
  analyze_wildcard boolean
  
  If true, the query attempts to analyze wildcard terms in the query string.
  
  auto_generate_synonyms_phrase_query boolean
  
  If true, the parser creates a match_phrase query for each multi-position token.
  
  default_operator string
  
  Values are and, AND, or, or OR.
  
  fields array[string]
  
  Array of fields you wish to search. Accepts wildcard expressions. You also can boost relevance scores for matches to particular fields using a caret (^) notation. Defaults to the index.query.default_field index setting, which has a default value of *.
  
  flags
  
  fuzzy_max_expansions number
  
  Maximum number of terms to which the query expands for fuzzy matching.
  
  fuzzy_prefix_length number
  
  Number of beginning characters left unchanged for fuzzy matching.
  
  fuzzy_transpositions boolean
  
  If true, edits for fuzzy matching include transpositions of two adjacent characters (for example, ab to ba).
  
  lenient boolean
  
  If true, format-based errors, such as providing a text value for a numeric field, are ignored.
  
  minimum_should_match number | string
  
  The minimum number of terms that should match as integer, percentage or range
  
  One of:
  MinimumShouldMatch number MinimumShouldMatch string
  
  query string Required
  
  Query string in the simple query string syntax you wish to parse and use for search.
  
  quote_field_suffix string
  
  Suffix appended to quoted text in the query string.
  
  span_containing object
  
  Hide span_containing attributes Show span_containing attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  big object Required
  
  Hide big attributes Show big attributes object
  
  span_gap object
  
  Can only be used as a clause in a span_near query.
  
  span_term object
  
  The equivalent of the term query but for use with other span queries.
  
  little object Required
  
  Hide little attributes Show little attributes object
  
  span_gap object
  
  Can only be used as a clause in a span_near query.
  
  span_term object
  
  The equivalent of the term query but for use with other span queries.
  
  span_field_masking object
  
  Hide span_field_masking attributes Show span_field_masking attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  field string Required
  
  Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.
  
  query object Required
  
  Hide query attributes Show query attributes object
  
  span_gap object
  
  Can only be used as a clause in a span_near query.
  
  span_term object
  
  The equivalent of the term query but for use with other span queries.
  
  span_first object
  
  Hide span_first attributes Show span_first attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  end number Required
  
  Controls the maximum end position permitted in a match.
  
  match object Required
  
  Hide match attributes Show match attributes object
  
  span_gap object
  
  Can only be used as a clause in a span_near query.
  
  span_term object
  
  The equivalent of the term query but for use with other span queries.
  
  span_multi object
  
  Hide span_multi attributes Show span_multi attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  match object Required
  
  An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  
  span_near object
  
  Hide span_near attributes Show span_near attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  clauses array[object] Required
  
  Array of one or more other span type queries.
  
  in_order boolean
  
  Controls whether matches are required to be in-order.
  
  slop number
  
  Controls the maximum number of intervening unmatched positions permitted.
  
  span_not object
  
  Hide span_not attributes Show span_not attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  dist number
  
  The number of tokens from within the include span that can’t have overlap with the exclude span. Equivalent to setting both pre and post.
  
  exclude object Required
  
  Hide exclude attributes Show exclude attributes object
  
  span_gap object
  
  Can only be used as a clause in a span_near query.
  
  span_term object
  
  The equivalent of the term query but for use with other span queries.
  
  include object Required
  
  Hide include attributes Show include attributes object
  
  span_gap object
  
  Can only be used as a clause in a span_near query.
  
  span_term object
  
  The equivalent of the term query but for use with other span queries.
  
  post number
  
  The number of tokens after the include span that can’t have overlap with the exclude span.
  
  pre number
  
  The number of tokens before the include span that can’t have overlap with the exclude span.
  
  span_or object
  
  Hide span_or attributes Show span_or attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  clauses array[object] Required
  
  Array of one or more other span type queries.
  
  span_term object
  
  Matches spans containing a term.
  
  External documentation
  
  span_within object
  
  Hide span_within attributes Show span_within attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  big object Required
  
  Hide big attributes Show big attributes object
  
  span_gap object
  
  Can only be used as a clause in a span_near query.
  
  span_term object
  
  The equivalent of the term query but for use with other span queries.
  
  little object Required
  
  Hide little attributes Show little attributes object
  
  span_gap object
  
  Can only be used as a clause in a span_near query.
  
  span_term object
  
  The equivalent of the term query but for use with other span queries.
  
  sparse_vector object
  
  Hide sparse_vector attributes Show sparse_vector attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  field string Required
  
  Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.
  
  query string
  
  The query text you want to use for search. If inference_id is specified, query must also be specified.
  
  prune boolean Technical preview; Added in 8.15.0
  
  Whether to perform pruning, omitting the non-significant tokens from the query to improve query performance. If prune is true but the pruning_config is not specified, pruning will occur but default values will be used. Default: false
  
  pruning_config object
  
  query_vector object
  
  Dictionary of precomputed sparse vectors and their associated weights. Only one of inference_id or query_vector may be supplied in a request.
  
  inference_id string
  
  term object
  
  Returns documents that contain an exact term in a provided field. To return a document, the query term must exactly match the queried field's value, including whitespace and capitalization.
  
  External documentation
  
  terms object
  
  Hide terms attributes Show terms attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  terms_set object
  
  Returns documents that contain a minimum number of exact terms in a provided field. To return a document, a required number of terms must exactly match the field values, including whitespace and capitalization.
  
  External documentation
  
  text_expansion object Deprecated Generally available; Added in 8.8.0
  
  Uses a natural language processing model to convert the query text into a list of token-weight pairs which are then used in a query against a sparse vector or rank features field.
  
  External documentation
  
  weighted_tokens object Deprecated Generally available; Added in 8.13.0
  
  Supports returning text_expansion query results by sending in precomputed tokens with the query.
  
  External documentation
  
  wildcard object
  
  Returns documents that contain terms matching a wildcard pattern.
  
  External documentation
  
  wrapper object
  
  Hide wrapper attributes Show wrapper attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  query string Required
  
  A base64 encoded query. The binary data format can be any of JSON, YAML, CBOR or SMILE encodings
  
  type object
  
  Hide type attributes Show type attributes object
  
  boost number
  
  Floating point number used to decrease or increase the relevance scores of the query. Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 increases the relevance score.
  
  _name string
  
  value string Required
  
  runtime_mappings object
  
  Hide runtime_mappings attribute Show runtime_mappings attribute object
  
  * object Additional properties
  
  Hide * attributes Show * attributes object
  
  fields object
  
  For type composite
  
  Hide fields attribute Show fields attribute object
  
  * object Additional properties
  
  Hide * attribute Show * attribute object
  
  type string Required
  
  Values are boolean, composite, date, double, geo_point, geo_shape, ip, keyword, long, or lookup.
  
  fetch_fields array[object]
  
  For type lookup
  
  Hide fetch_fields attributes Show fetch_fields attributes object
  
  field string Required
  
  Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.
  
  format string
  
  format string
  
  A custom format for date type runtime fields.
  
  input_field string
  
  Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.
  
  target_field string
  
  Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.
  
  target_index string
  
  script object
  
  Hide script attributes Show script attributes object
  
  source string | object
  
  One of:
  ScriptSource string SearchRequestBody object
  
  id string
  
  params object
  
  Specifies any named parameters that are passed into the script as variables. Use parameters instead of hard-coded values to decrease compile time.
  
  Hide params attribute Show params attribute object
  
  * object Additional properties
  
  lang string
  
  Any of:
  ScriptLanguage string ScriptLanguage string
  
  Values are painless, expression, mustache, or java.
  
  options object
  
  Hide options attribute Show options attribute object
  
  * string Additional properties
  
  type string Required
  
  Values are boolean, composite, date, double, geo_point, geo_shape, ip, keyword, long, or lookup.
  
  _source object
  
  Hide _source attributes Show _source attributes object
  
  includes array[string]
  
  An array of strings that defines the fields that will be excluded from the analysis. You do not need to add fields with unsupported data types to excludes, these fields are excluded from the analysis automatically.
  
  excludes array[string]
  
  An array of strings that defines the fields that will be included in the analysis.
- analysis object Required
  Hide analysis attributes Show analysis attributes object
  
  classification object
  
  Hide classification attributes Show classification attributes object
  
  alpha number
  
  Advanced configuration option. Machine learning uses loss guided tree growing, which means that the decision trees grow where the regularized loss decreases most quickly. This parameter affects loss calculations by acting as a multiplier of the tree depth. Higher alpha values result in shallower trees and faster training times. By default, this value is calculated during hyperparameter optimization. It must be greater than or equal to zero.
  
  dependent_variable string Required
  
  Defines which field of the document is to be predicted. It must match one of the fields in the index being used to train. If this field is missing from a document, then that document will not be used for training, but a prediction with the trained model will be generated for it. It is also known as continuous target variable. For classification analysis, the data type of the field must be numeric (integer, short, long, byte), categorical (ip or keyword), or boolean. There must be no more than 30 different values in this field. For regression analysis, the data type of the field must be numeric.
  
  downsample_factor number
  
  Advanced configuration option. Controls the fraction of data that is used to compute the derivatives of the loss function for tree training. A small value results in the use of a small fraction of the data. If this value is set to be less than 1, accuracy typically improves. However, too small a value may result in poor convergence for the ensemble and so require more trees. By default, this value is calculated during hyperparameter optimization. It must be greater than zero and less than or equal to 1.
  
  early_stopping_enabled boolean
  
  Advanced configuration option. Specifies whether the training process should finish if it is not finding any better performing models. If disabled, the training process can take significantly longer and the chance of finding a better performing model is unremarkable.
  
  eta number
  
  Advanced configuration option. The shrinkage applied to the weights. Smaller values result in larger forests which have a better generalization error. However, larger forests cause slower training. By default, this value is calculated during hyperparameter optimization. It must be a value between 0.001 and 1.
  
  eta_growth_rate_per_tree number
  
  Advanced configuration option. Specifies the rate at which eta increases for each new tree that is added to the forest. For example, a rate of 1.05 increases eta by 5% for each extra tree. By default, this value is calculated during hyperparameter optimization. It must be between 0.5 and 2.
  
  feature_bag_fraction number
  
  Advanced configuration option. Defines the fraction of features that will be used when selecting a random bag for each candidate split. By default, this value is calculated during hyperparameter optimization.
  
  feature_processors array[object]
  
  Advanced configuration option. A collection of feature preprocessors that modify one or more included fields. The analysis uses the resulting one or more features instead of the original document field. However, these features are ephemeral; they are not stored in the destination index. Multiple feature_processors entries can refer to the same document fields. Automatic categorical feature encoding still occurs for the fields that are unprocessed by a custom processor or that have categorical values. Use this property only if you want to override the automatic feature encoding of the specified fields.
  
  Hide feature_processors attributes Show feature_processors attributes object
  
  frequency_encoding object
  
  multi_encoding object
  
  n_gram_encoding object
  
  one_hot_encoding object
  
  target_mean_encoding object
  
  gamma number
  
  Advanced configuration option. Regularization parameter to prevent overfitting on the training data set. Multiplies a linear penalty associated with the size of individual trees in the forest. A high gamma value causes training to prefer small trees. A small gamma value results in larger individual trees and slower training. By default, this value is calculated during hyperparameter optimization. It must be a nonnegative value.
  
  lambda number
  
  Advanced configuration option. Regularization parameter to prevent overfitting on the training data set. Multiplies an L2 regularization term which applies to leaf weights of the individual trees in the forest. A high lambda value causes training to favor small leaf weights. This behavior makes the prediction function smoother at the expense of potentially not being able to capture relevant relationships between the features and the dependent variable. A small lambda value results in large individual trees and slower training. By default, this value is calculated during hyperparameter optimization. It must be a nonnegative value.
  
  max_optimization_rounds_per_hyperparameter number
  
  Advanced configuration option. A multiplier responsible for determining the maximum number of hyperparameter optimization steps in the Bayesian optimization procedure. The maximum number of steps is determined based on the number of undefined hyperparameters times the maximum optimization rounds per hyperparameter. By default, this value is calculated during hyperparameter optimization.
  
  max_trees number
  
  Advanced configuration option. Defines the maximum number of decision trees in the forest. The maximum value is 2000. By default, this value is calculated during hyperparameter optimization.
  
  num_top_feature_importance_values number
  
  Advanced configuration option. Specifies the maximum number of feature importance values per document to return. By default, no feature importance calculation occurs.
  
  prediction_field_name string
  
  Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.
  
  randomize_seed number
  
  Defines the seed for the random generator that is used to pick training data. By default, it is randomly generated. Set it to a specific value to use the same training data each time you start a job (assuming other related parameters such as source and analyzed_fields are the same).
  
  soft_tree_depth_limit number
  
  Advanced configuration option. Machine learning uses loss guided tree growing, which means that the decision trees grow where the regularized loss decreases most quickly. This soft limit combines with the soft_tree_depth_tolerance to penalize trees that exceed the specified depth; the regularized loss increases quickly beyond this depth. By default, this value is calculated during hyperparameter optimization. It must be greater than or equal to 0.
  
  soft_tree_depth_tolerance number
  
  Advanced configuration option. This option controls how quickly the regularized loss increases when the tree depth exceeds soft_tree_depth_limit. By default, this value is calculated during hyperparameter optimization. It must be greater than or equal to 0.01.
  
  training_percent string | number
  
  One of:
  Percentage string Percentage number
  
  class_assignment_objective string
  
  num_top_classes number
  
  Defines the number of categories for which the predicted probabilities are reported. It must be non-negative or -1. If it is -1 or greater than the total number of categories, probabilities are reported for all categories; if you have a large number of categories, there could be a significant effect on the size of your destination index. NOTE: To use the AUC ROC evaluation method, num_top_classes must be set to -1 or a value greater than or equal to the total number of categories.
  
  outlier_detection object
  
  Hide outlier_detection attributes Show outlier_detection attributes object
  
  compute_feature_influence boolean
  
  Specifies whether the feature influence calculation is enabled.
  
  feature_influence_threshold number
  
  The minimum outlier score that a document needs to have in order to calculate its feature influence score. Value range: 0-1.
  
  method string
  
  The method that outlier detection uses. Available methods are lof, ldof, distance_kth_nn, distance_knn, and ensemble. The default value is ensemble, which means that outlier detection uses an ensemble of different methods and normalises and combines their individual outlier scores to obtain the overall outlier score.
  
  n_neighbors number
  
  Defines the value for how many nearest neighbors each method of outlier detection uses to calculate its outlier score. When the value is not set, different values are used for different ensemble members. This default behavior helps improve the diversity in the ensemble; only override it if you are confident that the value you choose is appropriate for the data set.
  
  outlier_fraction number
  
  The proportion of the data set that is assumed to be outlying prior to outlier detection. For example, 0.05 means it is assumed that 5% of values are real outliers and 95% are inliers.
  
  standardization_enabled boolean
  
  If true, the following operation is performed on the columns before computing outlier scores: (x_i - mean(x_i)) / sd(x_i).
  
  regression object
  
  Hide regression attributes Show regression attributes object
  
  alpha number
  
  Advanced configuration option. Machine learning uses loss guided tree growing, which means that the decision trees grow where the regularized loss decreases most quickly. This parameter affects loss calculations by acting as a multiplier of the tree depth. Higher alpha values result in shallower trees and faster training times. By default, this value is calculated during hyperparameter optimization. It must be greater than or equal to zero.
  
  dependent_variable string Required
  
  Defines which field of the document is to be predicted. It must match one of the fields in the index being used to train. If this field is missing from a document, then that document will not be used for training, but a prediction with the trained model will be generated for it. It is also known as continuous target variable. For classification analysis, the data type of the field must be numeric (integer, short, long, byte), categorical (ip or keyword), or boolean. There must be no more than 30 different values in this field. For regression analysis, the data type of the field must be numeric.
  
  downsample_factor number
  
  Advanced configuration option. Controls the fraction of data that is used to compute the derivatives of the loss function for tree training. A small value results in the use of a small fraction of the data. If this value is set to be less than 1, accuracy typically improves. However, too small a value may result in poor convergence for the ensemble and so require more trees. By default, this value is calculated during hyperparameter optimization. It must be greater than zero and less than or equal to 1.
  
  early_stopping_enabled boolean
  
  Advanced configuration option. Specifies whether the training process should finish if it is not finding any better performing models. If disabled, the training process can take significantly longer and the chance of finding a better performing model is unremarkable.
  
  eta number
  
  Advanced configuration option. The shrinkage applied to the weights. Smaller values result in larger forests which have a better generalization error. However, larger forests cause slower training. By default, this value is calculated during hyperparameter optimization. It must be a value between 0.001 and 1.
  
  eta_growth_rate_per_tree number
  
  Advanced configuration option. Specifies the rate at which eta increases for each new tree that is added to the forest. For example, a rate of 1.05 increases eta by 5% for each extra tree. By default, this value is calculated during hyperparameter optimization. It must be between 0.5 and 2.
  
  feature_bag_fraction number
  
  Advanced configuration option. Defines the fraction of features that will be used when selecting a random bag for each candidate split. By default, this value is calculated during hyperparameter optimization.
  
  feature_processors array[object]
  
  Advanced configuration option. A collection of feature preprocessors that modify one or more included fields. The analysis uses the resulting one or more features instead of the original document field. However, these features are ephemeral; they are not stored in the destination index. Multiple feature_processors entries can refer to the same document fields. Automatic categorical feature encoding still occurs for the fields that are unprocessed by a custom processor or that have categorical values. Use this property only if you want to override the automatic feature encoding of the specified fields.
  
  Hide feature_processors attributes Show feature_processors attributes object
  
  frequency_encoding object
  
  multi_encoding object
  
  n_gram_encoding object
  
  one_hot_encoding object
  
  target_mean_encoding object
  
  gamma number
  
  Advanced configuration option. Regularization parameter to prevent overfitting on the training data set. Multiplies a linear penalty associated with the size of individual trees in the forest. A high gamma value causes training to prefer small trees. A small gamma value results in larger individual trees and slower training. By default, this value is calculated during hyperparameter optimization. It must be a nonnegative value.
  
  lambda number
  
  Advanced configuration option. Regularization parameter to prevent overfitting on the training data set. Multiplies an L2 regularization term which applies to leaf weights of the individual trees in the forest. A high lambda value causes training to favor small leaf weights. This behavior makes the prediction function smoother at the expense of potentially not being able to capture relevant relationships between the features and the dependent variable. A small lambda value results in large individual trees and slower training. By default, this value is calculated during hyperparameter optimization. It must be a nonnegative value.
  
  max_optimization_rounds_per_hyperparameter number
  
  Advanced configuration option. A multiplier responsible for determining the maximum number of hyperparameter optimization steps in the Bayesian optimization procedure. The maximum number of steps is determined based on the number of undefined hyperparameters times the maximum optimization rounds per hyperparameter. By default, this value is calculated during hyperparameter optimization.
  
  max_trees number
  
  Advanced configuration option. Defines the maximum number of decision trees in the forest. The maximum value is 2000. By default, this value is calculated during hyperparameter optimization.
  
  num_top_feature_importance_values number
  
  Advanced configuration option. Specifies the maximum number of feature importance values per document to return. By default, no feature importance calculation occurs.
  
  prediction_field_name string
  
  Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.
  
  randomize_seed number
  
  Defines the seed for the random generator that is used to pick training data. By default, it is randomly generated. Set it to a specific value to use the same training data each time you start a job (assuming other related parameters such as source and analyzed_fields are the same).
  
  soft_tree_depth_limit number
  
  Advanced configuration option. Machine learning uses loss guided tree growing, which means that the decision trees grow where the regularized loss decreases most quickly. This soft limit combines with the soft_tree_depth_tolerance to penalize trees that exceed the specified depth; the regularized loss increases quickly beyond this depth. By default, this value is calculated during hyperparameter optimization. It must be greater than or equal to 0.
  
  soft_tree_depth_tolerance number
  
  Advanced configuration option. This option controls how quickly the regularized loss increases when the tree depth exceeds soft_tree_depth_limit. By default, this value is calculated during hyperparameter optimization. It must be greater than or equal to 0.01.
  
  training_percent string | number
  
  One of:
  Percentage string Percentage number
  
  loss_function string
  
  The loss function used during regression. Available options are mse (mean squared error), msle (mean squared logarithmic error), huber (Pseudo-Huber loss).
  
  loss_function_parameter number
  
  A positive number that is used as a parameter to the loss_function.
- model_memory_limit string
- max_num_threads number
- analyzed_fields object
  Hide analyzed_fields attributes Show analyzed_fields attributes object
  
  includes array[string]
  
  An array of strings that defines the fields that will be excluded from the analysis. You do not need to add fields with unsupported data types to excludes, these fields are excluded from the analysis automatically.
  
  excludes array[string]
  
  An array of strings that defines the fields that will be included in the analysis.

Responses

200 application/json
Hide response attribute Show response attribute object
- feature_values array[object] Required
  
  An array of objects that contain feature name and value pairs. The features have been processed and indicate what will be sent to the model for training.
  
  Hide feature_values attribute Show feature_values attribute object
  
  * string Additional properties

POST /_ml/data_frame/analytics/{id}/_preview

POST _ml/data_frame/analytics/_preview
{
  "config": {
    "source": {
      "index": "houses_sold_last_10_yrs"
    },
    "analysis": {
      "regression": {
        "dependent_variable": "price"
      }
    }
  }
}

curl \
 --request POST 'http://api.example.com/_ml/data_frame/analytics/{id}/_preview' \
 --header "Content-Type: application/json" \
 --data '"{\n  \"config\": {\n    \"source\": {\n      \"index\": \"houses_sold_last_10_yrs\"\n    },\n    \"analysis\": {\n      \"regression\": {\n        \"dependent_variable\": \"price\"\n      }\n    }\n  }\n}"'

Request example

An example body for a `POST _ml/data_frame/analytics/_preview` request.

{
  "config": {
    "source": {
      "index": "houses_sold_last_10_yrs"
    },
    "analysis": {
      "regression": {
        "dependent_variable": "price"
      }
    }
  }
}

Documentation preview

This is a preview of your version @2025-06-09 which is not yet released.

View current documentation

Preview features used by data frame analytics Generally available; Added in 7.13.0

Path parameters

Body

filter object | array[object]

minimum_should_match number | string

must object | array[object]

must_not object | array[object]

should object | array[object]

minimum_should_match number | string

distance_feature object

values string | array[string]

filter object | array[object]

minimum_should_match number | string

stop_words string | array[string]

fuzziness string | number

minimum_should_match number | string

fuzziness string | number

minimum_should_match number | string

ruleset_ids string | array[string]

minimum_should_match number | string

source string | object

lang string

training_percent string | number

training_percent string | number

Responses

Documentation preview