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MlModel
This schema defines the Model entity. Models are algorithms trained on data to find patterns or make predictions.
$id:https://open-metadata.org/schema/entity/data/mlmodel.json
Type: object
This schema does not accept additional properties.
Properties
- id required- Unique identifier of an ML Model instance.
- $ref: ../../type/basic.json#/definitions/uuid
 
- name required- Name that identifies this ML Model.
- Type: string
- Length: between 1 and 128
 
- fullyQualifiedName
- A unique name that identifies an ML Model.
- Type: string
- Length: between 1 and 256
 
- displayName
- Display Name that identifies this ML Model.
- Type: string
 
- description
- Description of the ML Model, what it is, and how to use it.
- Type: string
 
- algorithm required- Algorithm used to train the ML Model.
- Type: string
 
- mlFeatures
- Features used to train the ML Model.
- Type: array- Items
- $ref: #/definitions/mlFeature
 
 
- mlHyperParameters
- Hyper Parameters used to train the ML Model.
- Type: array- Items
- $ref: #/definitions/mlHyperParameter
 
 
- target
- For supervised ML Models, the value to estimate.
- $ref: #/definitions/featureName
 
- dashboard
- Performance Dashboard URL to track metric evolution.
- $ref: ../../type/entityReference.json
 
- mlStore
- Location containing the ML Model. It can be a storage layer and/or a container repository.
- $ref: #/definitions/mlStore
 
- server
- Endpoint that makes the ML Model available, e.g,. a REST API serving the data or computing predictions.
- $ref: ../../type/basic.json#/definitions/href
 
- href
- Link to the resource corresponding to this entity.
- $ref: ../../type/basic.json#/definitions/href
 
- owner
- Owner of this ML Model.
- $ref: ../../type/entityReference.json
 
- followers
- Followers of this ML Model.
- $ref: ../../type/entityReference.json#/definitions/entityReferenceList
 
- tags
- Tags for this ML Model.
- Type: array- Items
- $ref: ../../type/tagLabel.json
 
 
- usageSummary
- Latest usage information for this ML Model.
- $ref: ../../type/usageDetails.json
 
- version
- Metadata version of the entity.
- $ref: ../../type/entityHistory.json#/definitions/entityVersion
 
- updatedAt
- Last update time corresponding to the new version of the entity in Unix epoch time milliseconds.
- $ref: ../../type/basic.json#/definitions/timestamp
 
- updatedBy
- User who made the update.
- Type: string
 
- changeDescription
- Change that lead to this version of the entity.
- $ref: ../../type/entityHistory.json#/definitions/changeDescription
 
- deleted
- When trueindicates the entity has been soft deleted.
- Type: boolean
- Default: false
 
- When 
Type definitions in this schema
featureType
- This enum defines the type of data stored in a ML Feature.
- Type: string
- The value is restricted to the following:
- "numerical"
- "categorical"
 
featureSourceDataType
- This enum defines the type of data of a ML Feature source.
- Type: string
- The value is restricted to the following:
- "integer"
- "number"
- "string"
- "array"
- "date"
- "timestamp"
- "object"
- "boolean"
 
featureName
- Local name (not fully qualified name) of the ML Feature.
- Type: string
- The value must match this pattern: ^[^.]*$
- Length: between 1 and 128
featureSourceName
- Local name (not fully qualified name) of a ML Feature source.
- Type: string
- The value must match this pattern: ^[^.]*$
- Length: between 1 and 128
fullyQualifiedFeatureSourceName
- Fully qualified name of the ML Feature Source that includes serviceName.[databaseName].tableName/fileName/apiName.columnName[.nestedColumnName].
- Type: string
- Length: between 1 and 256
fullyQualifiedFeatureName
- Fully qualified name of the ML Feature that includes modelName.featureName.
- Type: string
- Length: between 1 and 256
featureSource
- This schema defines the sources of a ML Feature.
- Type: object
- This schema does not accept additional properties.
- Properties
- name
- dataType
- Data type of the source (int, date etc.).
- $ref: #/definitions/featureSourceDataType
 
- description
- Description of the feature source.
- Type: string
 
- fullyQualifiedName
- dataSource
- Description of the Data Source (e.g., a Table).
- $ref: ../../type/entityReference.json
 
- tags
- Tags associated with the feature source.
- Type: array- Items
- $ref: ../../type/tagLabel.json
 
 
 
mlFeature
- This schema defines the type for an ML Feature used in an ML Model.
- Type: object
- This schema does not accept additional properties.
- Properties
- name
- dataType
- Data type of the column (numerical vs. categorical).
- $ref: #/definitions/featureType
 
- description
- Description of the ML Feature.
- Type: string
 
- fullyQualifiedName
- featureSources
- Columns used to create the ML Feature.
- Type: array- Items
- $ref: #/definitions/featureSource
 
 
- featureAlgorithm
- Description of the algorithm used to compute the feature, e.g., PCA, bucketing...
- Type: string
 
- tags
- Tags associated with the feature.
- Type: array- Items
- $ref: ../../type/tagLabel.json
 
 
 
mlHyperParameter
- This schema defines the type for an ML HyperParameter used in an ML Model.
- Type: object
- This schema does not accept additional properties.
- Properties
- name
- Hyper parameter name.
- Type: string
 
- value
- Hyper parameter value.
- Type: string
 
- description
- Description of the Hyper Parameter.
- Type: string
 
 
- name
mlStore
- Location containing the ML Model. It can be a storage layer and/or a container repository.
- Type: object
- This schema does not accept additional properties.
- Properties
- storage
- Storage Layer containing the ML Model data.
- $ref: ../../type/basic.json#/definitions/href
 
- imageRepository
- Container Repository with the ML Model image.
- $ref: ../../type/basic.json#/definitions/href
 
 
- storage
This document was updated on: Wednesday, March 9, 2022
