Moodle PHP Documentation 4.3
Moodle 4.3.5 (Build: 20240610) (7dcfaa79f78)
Google_Service_Prediction_Trainedmodels_Resource Class Reference

The "trainedmodels" collection of methods. More...

Inheritance diagram for Google_Service_Prediction_Trainedmodels_Resource:
Google_Service_Resource

Public Member Functions

 analyze ($project, $id, $optParams=array())
 Get analysis of the model and the data the model was trained on.
 
 call ($name, $arguments, $expected_class=null)
 TODO: This function needs simplifying.
 
 delete ($project, $id, $optParams=array())
 Delete a trained model.
 
 get ($project, $id, $optParams=array())
 Check training status of your model.
 
 insert ($project, Google_Service_Prediction_Insert $postBody, $optParams=array())
 Train a Prediction API model.
 
 listTrainedmodels ($project, $optParams=array())
 List available models.
 
 predict ($project, $id, Google_Service_Prediction_Input $postBody, $optParams=array())
 Submit model id and request a prediction.
 
 update ($project, $id, Google_Service_Prediction_Update $postBody, $optParams=array())
 Add new data to a trained model.
 

Protected Member Functions

 convertToArrayAndStripNulls ($o)
 

Detailed Description

The "trainedmodels" collection of methods.

Typical usage is: $predictionService = new Google_Service_Prediction(...); $trainedmodels = $predictionService->trainedmodels;

Member Function Documentation

◆ analyze()

Google_Service_Prediction_Trainedmodels_Resource::analyze ( $project,
$id,
$optParams = array() )

Get analysis of the model and the data the model was trained on.

(trainedmodels.analyze)

Parameters
string$projectThe project associated with the model.
string$idThe unique name for the predictive model.
array$optParamsOptional parameters.
Return values
Google_Service_Prediction_Analyze

◆ call()

Google_Service_Resource::call ( $name,
$arguments,
$expected_class = null )
inherited

TODO: This function needs simplifying.

Parameters
$name
$arguments
$expected_class- optional, the expected class name
Return values
Google_Http_Request|expected_class
Exceptions
Google_Exception

◆ delete()

Google_Service_Prediction_Trainedmodels_Resource::delete ( $project,
$id,
$optParams = array() )

Delete a trained model.

(trainedmodels.delete)

Parameters
string$projectThe project associated with the model.
string$idThe unique name for the predictive model.
array$optParamsOptional parameters.

◆ get()

Google_Service_Prediction_Trainedmodels_Resource::get ( $project,
$id,
$optParams = array() )

Check training status of your model.

(trainedmodels.get)

Parameters
string$projectThe project associated with the model.
string$idThe unique name for the predictive model.
array$optParamsOptional parameters.
Return values
Google_Service_Prediction_Insert2

◆ insert()

Google_Service_Prediction_Trainedmodels_Resource::insert ( $project,
Google_Service_Prediction_Insert $postBody,
$optParams = array() )

Train a Prediction API model.

(trainedmodels.insert)

Parameters
string$projectThe project associated with the model.
Google_Insert$postBody
array$optParamsOptional parameters.
Return values
Google_Service_Prediction_Insert2

◆ listTrainedmodels()

Google_Service_Prediction_Trainedmodels_Resource::listTrainedmodels ( $project,
$optParams = array() )

List available models.

(trainedmodels.listTrainedmodels)

Parameters
string$projectThe project associated with the model.
array$optParamsOptional parameters.

@opt_param string pageToken Pagination token. @opt_param string maxResults Maximum number of results to return.

Return values
Google_Service_Prediction_PredictionList

◆ predict()

Google_Service_Prediction_Trainedmodels_Resource::predict ( $project,
$id,
Google_Service_Prediction_Input $postBody,
$optParams = array() )

Submit model id and request a prediction.

(trainedmodels.predict)

Parameters
string$projectThe project associated with the model.
string$idThe unique name for the predictive model.
Google_Input$postBody
array$optParamsOptional parameters.
Return values
Google_Service_Prediction_Output

◆ update()

Google_Service_Prediction_Trainedmodels_Resource::update ( $project,
$id,
Google_Service_Prediction_Update $postBody,
$optParams = array() )

Add new data to a trained model.

(trainedmodels.update)

Parameters
string$projectThe project associated with the model.
string$idThe unique name for the predictive model.
Google_Update$postBody
array$optParamsOptional parameters.
Return values
Google_Service_Prediction_Insert2

The documentation for this class was generated from the following file: