Documentation

Google_Service_Prediction_Resource_Trainedmodels extends Google_Service_Resource
in package

Application

The "trainedmodels" collection of methods.

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

$client : Google_Client
$methods : array<string|int, mixed>
$resourceName : string
$rootUrl : string
$serviceName : string
$servicePath : string
$stackParameters : mixed
__construct() : mixed
analyze() : Google_Service_Prediction_Analyze: Get analysis of the model and the data the model was trained on.
call() : Google_Http_Request|expectedClass: TODO: This function needs simplifying.
createRequestUri() : string: Parse/expand request parameters and create a fully qualified request uri.
delete() : mixed: Delete a trained model. (trainedmodels.delete)
get() : Google_Service_Prediction_Insert2: Check training status of your model. (trainedmodels.get)
insert() : Google_Service_Prediction_Insert2: Train a Prediction API model. (trainedmodels.insert)
listTrainedmodels() : Google_Service_Prediction_PredictionList: List available models. (trainedmodels.listTrainedmodels)
predict() : Google_Service_Prediction_Output: Submit model id and request a prediction. (trainedmodels.predict)
update() : Google_Service_Prediction_Insert2: Add new data to a trained model. (trainedmodels.update)
convertToArrayAndStripNulls() : mixed

$client


    private
        Google_Client
    $client

$methods


    private
        array<string|int, mixed>
    $methods

$resourceName


    private
        string
    $resourceName

$rootUrl


    private
        string
    $rootUrl

$serviceName


    private
        string
    $serviceName

$servicePath


    private
        string
    $servicePath

$stackParameters


    private
        mixed
    $stackParameters
     = array('alt' => array('type' => 'string', 'location' => 'query'), 'fields' => array('type' => 'string', 'location' => 'query'), 'trace' => array('type' => 'string', 'location' => 'query'), 'userIp' => array('type' => 'string', 'location' => 'query'), 'quotaUser' => array('type' => 'string', 'location' => 'query'), 'data' => array('type' => 'string', 'location' => 'body'), 'mimeType' => array('type' => 'string', 'location' => 'header'), 'uploadType' => array('type' => 'string', 'location' => 'query'), 'mediaUpload' => array('type' => 'complex', 'location' => 'query'), 'prettyPrint' => array('type' => 'string', 'location' => 'query'))

__construct()


    public
                __construct(mixed $service, mixed $serviceName, mixed $resourceName, mixed $resource) : mixed

Parameters

$service : mixed
$serviceName : mixed
$resourceName : mixed
$resource : mixed

Return values

mixed —

analyze()

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


    public
                analyze(string $project, string $id[, array<string|int, mixed> $optParams = array() ]) : Google_Service_Prediction_Analyze

(trainedmodels.analyze)

Parameters

$project : string: The project associated with the model.
$id : string: The unique name for the predictive model.
$optParams : array<string|int, mixed> = array(): Optional parameters.

Return values

Google_Service_Prediction_Analyze —

call()

TODO: This function needs simplifying.


    public
                call( $name,  $arguments[,  $expectedClass = null ]) : Google_Http_Request|expectedClass

Parameters

$name :

$arguments :

$expectedClass : = null

optional, the expected class name

Return values

Google_Http_Request|expectedClass —

createRequestUri()

Parse/expand request parameters and create a fully qualified request uri.


    public
                createRequestUri(string $restPath, array<string|int, mixed> $params) : string

Parameters

$restPath : string
$params : array<string|int, mixed>

Return values

string —

$requestUrl

delete()

Delete a trained model. (trainedmodels.delete)


    public
                delete(string $project, string $id[, array<string|int, mixed> $optParams = array() ]) : mixed

Parameters

$project : string: The project associated with the model.
$id : string: The unique name for the predictive model.
$optParams : array<string|int, mixed> = array(): Optional parameters.

Return values

mixed —

get()

Check training status of your model. (trainedmodels.get)


    public
                get(string $project, string $id[, array<string|int, mixed> $optParams = array() ]) : Google_Service_Prediction_Insert2

Parameters

$project : string: The project associated with the model.
$id : string: The unique name for the predictive model.
$optParams : array<string|int, mixed> = array(): Optional parameters.

Return values

Google_Service_Prediction_Insert2 —

insert()

Train a Prediction API model. (trainedmodels.insert)


    public
                insert(string $project, Google_Service_Prediction_Insert $postBody[, array<string|int, mixed> $optParams = array() ]) : Google_Service_Prediction_Insert2

Parameters

$project : string: The project associated with the model.
$postBody : Google_Service_Prediction_Insert
$optParams : array<string|int, mixed> = array(): Optional parameters.

Return values

Google_Service_Prediction_Insert2 —

listTrainedmodels()

List available models. (trainedmodels.listTrainedmodels)


    public
                listTrainedmodels(string $project[, array<string|int, mixed> $optParams = array() ]) : Google_Service_Prediction_PredictionList

Parameters

$project : string: The project associated with the model.
$optParams : array<string|int, mixed> = array(): Optional parameters.

Return values

Google_Service_Prediction_PredictionList —

predict()

Submit model id and request a prediction. (trainedmodels.predict)


    public
                predict(string $project, string $id, Google_Service_Prediction_Input $postBody[, array<string|int, mixed> $optParams = array() ]) : Google_Service_Prediction_Output

Parameters

$project : string: The project associated with the model.
$id : string: The unique name for the predictive model.
$postBody : Google_Service_Prediction_Input
$optParams : array<string|int, mixed> = array(): Optional parameters.

Return values

Google_Service_Prediction_Output —

update()

Add new data to a trained model. (trainedmodels.update)


    public
                update(string $project, string $id, Google_Service_Prediction_Update $postBody[, array<string|int, mixed> $optParams = array() ]) : Google_Service_Prediction_Insert2

Parameters

$project : string: The project associated with the model.
$id : string: The unique name for the predictive model.
$postBody : Google_Service_Prediction_Update
$optParams : array<string|int, mixed> = array(): Optional parameters.

Return values

Google_Service_Prediction_Insert2 —

convertToArrayAndStripNulls()


    protected
                convertToArrayAndStripNulls(mixed $o) : mixed

Parameters

$o : mixed

Return values

mixed —