Reference documentation and code samples for the Retail V2 API class Google::Cloud::Retail::V2::Model.
Metadata that describes the training and serving parameters of a Model. A Model can be associated with a ServingConfig and then queried through the Predict API.
Inherits
- Object
Extended By
- Google::Protobuf::MessageExts::ClassMethods
Includes
- Google::Protobuf::MessageExts
Methods
#create_time
def create_time() -> ::Google::Protobuf::Timestamp
- (::Google::Protobuf::Timestamp) — Output only. Timestamp the Recommendation Model was created at.
#data_state
def data_state() -> ::Google::Cloud::Retail::V2::Model::DataState
-
(::Google::Cloud::Retail::V2::Model::DataState) — Output only. The state of data requirements for this model:
DATA_OK
andDATA_ERROR
.Recommendation model cannot be trained if the data is in
DATA_ERROR
state. Recommendation model can haveDATA_ERROR
state even if serving state isACTIVE
: models were trained successfully before, but cannot be refreshed because model no longer has sufficient data for training.
#display_name
def display_name() -> ::String
-
(::String) — Required. The display name of the model.
Should be human readable, used to display Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of 1024 characters.
#display_name=
def display_name=(value) -> ::String
-
value (::String) — Required. The display name of the model.
Should be human readable, used to display Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of 1024 characters.
-
(::String) — Required. The display name of the model.
Should be human readable, used to display Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of 1024 characters.
#filtering_option
def filtering_option() -> ::Google::Cloud::Retail::V2::RecommendationsFilteringOption
-
(::Google::Cloud::Retail::V2::RecommendationsFilteringOption) — Optional. If
RECOMMENDATIONS_FILTERING_ENABLED
, recommendation filtering by attributes is enabled for the model.
#filtering_option=
def filtering_option=(value) -> ::Google::Cloud::Retail::V2::RecommendationsFilteringOption
-
value (::Google::Cloud::Retail::V2::RecommendationsFilteringOption) — Optional. If
RECOMMENDATIONS_FILTERING_ENABLED
, recommendation filtering by attributes is enabled for the model.
-
(::Google::Cloud::Retail::V2::RecommendationsFilteringOption) — Optional. If
RECOMMENDATIONS_FILTERING_ENABLED
, recommendation filtering by attributes is enabled for the model.
#last_tune_time
def last_tune_time() -> ::Google::Protobuf::Timestamp
- (::Google::Protobuf::Timestamp) — Output only. The timestamp when the latest successful tune finished.
#model_features_config
def model_features_config() -> ::Google::Cloud::Retail::V2::Model::ModelFeaturesConfig
- (::Google::Cloud::Retail::V2::Model::ModelFeaturesConfig) — Optional. Additional model features config.
#model_features_config=
def model_features_config=(value) -> ::Google::Cloud::Retail::V2::Model::ModelFeaturesConfig
- value (::Google::Cloud::Retail::V2::Model::ModelFeaturesConfig) — Optional. Additional model features config.
- (::Google::Cloud::Retail::V2::Model::ModelFeaturesConfig) — Optional. Additional model features config.
#name
def name() -> ::String
-
(::String) — Required. The fully qualified resource name of the model.
Format:
projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}
catalog_id has char limit of 50. recommendation_model_id has char limit of 40.
#name=
def name=(value) -> ::String
-
value (::String) — Required. The fully qualified resource name of the model.
Format:
projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}
catalog_id has char limit of 50. recommendation_model_id has char limit of 40.
-
(::String) — Required. The fully qualified resource name of the model.
Format:
projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}
catalog_id has char limit of 50. recommendation_model_id has char limit of 40.
#optimization_objective
def optimization_objective() -> ::String
-
(::String) — Optional. The optimization objective e.g.
cvr
.Currently supported values:
ctr
,cvr
,revenue-per-order
.If not specified, we choose default based on model type. Default depends on type of recommendation:
recommended-for-you
=>ctr
others-you-may-like
=>ctr
frequently-bought-together
=>revenue_per_order
This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type =
frequently-bought-together
and optimization_objective =ctr
), you receive an error 400 if you try to create/update a recommendation with this set of knobs.
#optimization_objective=
def optimization_objective=(value) -> ::String
-
value (::String) — Optional. The optimization objective e.g.
cvr
.Currently supported values:
ctr
,cvr
,revenue-per-order
.If not specified, we choose default based on model type. Default depends on type of recommendation:
recommended-for-you
=>ctr
others-you-may-like
=>ctr
frequently-bought-together
=>revenue_per_order
This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type =
frequently-bought-together
and optimization_objective =ctr
), you receive an error 400 if you try to create/update a recommendation with this set of knobs.
-
(::String) — Optional. The optimization objective e.g.
cvr
.Currently supported values:
ctr
,cvr
,revenue-per-order
.If not specified, we choose default based on model type. Default depends on type of recommendation:
recommended-for-you
=>ctr
others-you-may-like
=>ctr
frequently-bought-together
=>revenue_per_order
This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type =
frequently-bought-together
and optimization_objective =ctr
), you receive an error 400 if you try to create/update a recommendation with this set of knobs.
#periodic_tuning_state
def periodic_tuning_state() -> ::Google::Cloud::Retail::V2::Model::PeriodicTuningState
-
(::Google::Cloud::Retail::V2::Model::PeriodicTuningState) — Optional. The state of periodic tuning.
The period we use is 3 months - to do a one-off tune earlier use the
TuneModel
method. Default value isPERIODIC_TUNING_ENABLED
.
#periodic_tuning_state=
def periodic_tuning_state=(value) -> ::Google::Cloud::Retail::V2::Model::PeriodicTuningState
-
value (::Google::Cloud::Retail::V2::Model::PeriodicTuningState) — Optional. The state of periodic tuning.
The period we use is 3 months - to do a one-off tune earlier use the
TuneModel
method. Default value isPERIODIC_TUNING_ENABLED
.
-
(::Google::Cloud::Retail::V2::Model::PeriodicTuningState) — Optional. The state of periodic tuning.
The period we use is 3 months - to do a one-off tune earlier use the
TuneModel
method. Default value isPERIODIC_TUNING_ENABLED
.
#serving_config_lists
def serving_config_lists() -> ::Array<::Google::Cloud::Retail::V2::Model::ServingConfigList>
- (::Array<::Google::Cloud::Retail::V2::Model::ServingConfigList>) — Output only. The list of valid serving configs associated with the PageOptimizationConfig.
#serving_state
def serving_state() -> ::Google::Cloud::Retail::V2::Model::ServingState
-
(::Google::Cloud::Retail::V2::Model::ServingState) — Output only. The serving state of the model:
ACTIVE
,NOT_ACTIVE
.
#training_state
def training_state() -> ::Google::Cloud::Retail::V2::Model::TrainingState
-
(::Google::Cloud::Retail::V2::Model::TrainingState) — Optional. The training state that the model is in (e.g.
TRAINING
orPAUSED
).Since part of the cost of running the service is frequency of training - this can be used to determine when to train model in order to control cost. If not specified: the default value for
CreateModel
method isTRAINING
. The default value forUpdateModel
method is to keep the state the same as before.
#training_state=
def training_state=(value) -> ::Google::Cloud::Retail::V2::Model::TrainingState
-
value (::Google::Cloud::Retail::V2::Model::TrainingState) — Optional. The training state that the model is in (e.g.
TRAINING
orPAUSED
).Since part of the cost of running the service is frequency of training - this can be used to determine when to train model in order to control cost. If not specified: the default value for
CreateModel
method isTRAINING
. The default value forUpdateModel
method is to keep the state the same as before.
-
(::Google::Cloud::Retail::V2::Model::TrainingState) — Optional. The training state that the model is in (e.g.
TRAINING
orPAUSED
).Since part of the cost of running the service is frequency of training - this can be used to determine when to train model in order to control cost. If not specified: the default value for
CreateModel
method isTRAINING
. The default value forUpdateModel
method is to keep the state the same as before.
#tuning_operation
def tuning_operation() -> ::String
-
(::String) — Output only. The tune operation associated with the model.
Can be used to determine if there is an ongoing tune for this recommendation. Empty field implies no tune is goig on.
#type
def type() -> ::String
-
(::String) — Required. The type of model e.g.
home-page
.Currently supported values:
recommended-for-you
,others-you-may-like
,frequently-bought-together
,page-optimization
,similar-items
,buy-it-again
,on-sale-items
, andrecently-viewed
(readonly value).This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type =
frequently-bought-together
and optimization_objective =ctr
), you receive an error 400 if you try to create/update a recommendation with this set of knobs.
#type=
def type=(value) -> ::String
-
value (::String) — Required. The type of model e.g.
home-page
.Currently supported values:
recommended-for-you
,others-you-may-like
,frequently-bought-together
,page-optimization
,similar-items
,buy-it-again
,on-sale-items
, andrecently-viewed
(readonly value).This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type =
frequently-bought-together
and optimization_objective =ctr
), you receive an error 400 if you try to create/update a recommendation with this set of knobs.
-
(::String) — Required. The type of model e.g.
home-page
.Currently supported values:
recommended-for-you
,others-you-may-like
,frequently-bought-together
,page-optimization
,similar-items
,buy-it-again
,on-sale-items
, andrecently-viewed
(readonly value).This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type =
frequently-bought-together
and optimization_objective =ctr
), you receive an error 400 if you try to create/update a recommendation with this set of knobs.
#update_time
def update_time() -> ::Google::Protobuf::Timestamp
- (::Google::Protobuf::Timestamp) — Output only. Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.