File "XPSClassificationEvaluationMetrics.php"
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<?php
/*
* Copyright 2014 Google Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License"); you may not
* use this file except in compliance with the License. You may obtain a copy of
* the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
* License for the specific language governing permissions and limitations under
* the License.
*/
namespace Google\Service\CloudNaturalLanguage;
class XPSClassificationEvaluationMetrics extends \Google\Collection
{
protected $collection_key = 'confidenceMetricsEntries';
/**
* The Area under precision recall curve metric.
*
* @var float
*/
public $auPrc;
/**
* The Area Under Receiver Operating Characteristic curve metric. Micro-
* averaged for the overall evaluation.
*
* @var float
*/
public $auRoc;
/**
* The Area under precision recall curve metric based on priors.
*
* @var float
*/
public $baseAuPrc;
protected $confidenceMetricsEntriesType = XPSConfidenceMetricsEntry::class;
protected $confidenceMetricsEntriesDataType = 'array';
protected $confusionMatrixType = XPSConfusionMatrix::class;
protected $confusionMatrixDataType = '';
/**
* The number of examples used for model evaluation.
*
* @var int
*/
public $evaluatedExamplesCount;
/**
* The Log Loss metric.
*
* @var float
*/
public $logLoss;
/**
* The Area under precision recall curve metric.
*
* @param float $auPrc
*/
public function setAuPrc($auPrc)
{
$this->auPrc = $auPrc;
}
/**
* @return float
*/
public function getAuPrc()
{
return $this->auPrc;
}
/**
* The Area Under Receiver Operating Characteristic curve metric. Micro-
* averaged for the overall evaluation.
*
* @param float $auRoc
*/
public function setAuRoc($auRoc)
{
$this->auRoc = $auRoc;
}
/**
* @return float
*/
public function getAuRoc()
{
return $this->auRoc;
}
/**
* The Area under precision recall curve metric based on priors.
*
* @param float $baseAuPrc
*/
public function setBaseAuPrc($baseAuPrc)
{
$this->baseAuPrc = $baseAuPrc;
}
/**
* @return float
*/
public function getBaseAuPrc()
{
return $this->baseAuPrc;
}
/**
* Metrics that have confidence thresholds. Precision-recall curve can be
* derived from it.
*
* @param XPSConfidenceMetricsEntry[] $confidenceMetricsEntries
*/
public function setConfidenceMetricsEntries($confidenceMetricsEntries)
{
$this->confidenceMetricsEntries = $confidenceMetricsEntries;
}
/**
* @return XPSConfidenceMetricsEntry[]
*/
public function getConfidenceMetricsEntries()
{
return $this->confidenceMetricsEntries;
}
/**
* Confusion matrix of the evaluation. Only set for MULTICLASS classification
* problems where number of annotation specs is no more than 10. Only set for
* model level evaluation, not for evaluation per label.
*
* @param XPSConfusionMatrix $confusionMatrix
*/
public function setConfusionMatrix(XPSConfusionMatrix $confusionMatrix)
{
$this->confusionMatrix = $confusionMatrix;
}
/**
* @return XPSConfusionMatrix
*/
public function getConfusionMatrix()
{
return $this->confusionMatrix;
}
/**
* The number of examples used for model evaluation.
*
* @param int $evaluatedExamplesCount
*/
public function setEvaluatedExamplesCount($evaluatedExamplesCount)
{
$this->evaluatedExamplesCount = $evaluatedExamplesCount;
}
/**
* @return int
*/
public function getEvaluatedExamplesCount()
{
return $this->evaluatedExamplesCount;
}
/**
* The Log Loss metric.
*
* @param float $logLoss
*/
public function setLogLoss($logLoss)
{
$this->logLoss = $logLoss;
}
/**
* @return float
*/
public function getLogLoss()
{
return $this->logLoss;
}
}
// Adding a class alias for backwards compatibility with the previous class name.
class_alias(XPSClassificationEvaluationMetrics::class, 'Google_Service_CloudNaturalLanguage_XPSClassificationEvaluationMetrics');