📄 Source: XPSConfidenceMetricsEntry.php
<?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 XPSConfidenceMetricsEntry extends \Google\Model
{
/**
* Metrics are computed with an assumption that the model never return
* predictions with score lower than this value.
*
* @var float
*/
public $confidenceThreshold;
/**
* The harmonic mean of recall and precision.
*
* @var float
*/
public $f1Score;
/**
* The harmonic mean of recall_at1 and precision_at1.
*
* @var float
*/
public $f1ScoreAt1;
/**
* The number of ground truth labels that are not matched by a model created
* label.
*
* @var string
*/
public $falseNegativeCount;
/**
* The number of model created labels that do not match a ground truth label.
*
* @var string
*/
public $falsePositiveCount;
/**
* False Positive Rate for the given confidence threshold.
*
* @var float
*/
public $falsePositiveRate;
/**
* The False Positive Rate when only considering the label that has the
* highest prediction score and not below the confidence threshold for each
* example.
*
* @var float
*/
public $falsePositiveRateAt1;
/**
* Metrics are computed with an assumption that the model always returns at
* most this many predictions (ordered by their score, descendingly), but they
* all still need to meet the confidence_threshold.
*
* @var int
*/
public $positionThreshold;
/**
* Precision for the given confidence threshold.
*
* @var float
*/
public $precision;
/**
* The precision when only considering the label that has the highest
* prediction score and not below the confidence threshold for each example.
*
* @var float
*/
public $precisionAt1;
/**
* Recall (true positive rate) for the given confidence threshold.
*
* @var float
*/
public $recall;
/**
* The recall (true positive rate) when only considering the label that has
* the highest prediction score and not below the confidence threshold for
* each example.
*
* @var float
*/
public $recallAt1;
/**
* The number of labels that were not created by the model, but if they would,
* they would not match a ground truth label.
*
* @var string
*/
public $trueNegativeCount;
/**
* The number of model created labels that match a ground truth label.
*
* @var string
*/
public $truePositiveCount;
/**
* Metrics are computed with an assumption that the model never return
* predictions with score lower than this value.
*
* @param float $confidenceThreshold
*/
public function setConfidenceThreshold($confidenceThreshold)
{
$this->confidenceThreshold = $confidenceThreshold;
}
/**
* @return float
*/
public function getConfidenceThreshold()
{
return $this->confidenceThreshold;
}
/**
* The harmonic mean of recall and precision.
*
* @param float $f1Score
*/
public function setF1Score($f1Score)
{
$this->f1Score = $f1Score;
}
/**
* @return float
*/
public function getF1Score()
{
return $this->f1Score;
}
/**
* The harmonic mean of recall_at1 and precision_at1.
*
* @param float $f1ScoreAt1
*/
public function setF1ScoreAt1($f1ScoreAt1)
{
$this->f1ScoreAt1 = $f1ScoreAt1;
}
/**
* @return float
*/
public function getF1ScoreAt1()
{
return $this->f1ScoreAt1;
}
/**
* The number of ground truth labels that are not matched by a model created
* label.
*
* @param string $falseNegativeCount
*/
public function setFalseNegativeCount($falseNegativeCount)
{
$this->falseNegativeCount = $falseNegativeCount;
}
/**
* @return string
*/
public function getFalseNegativeCount()
{
return $this->falseNegativeCount;
}
/**
* The number of model created labels that do not match a ground truth label.
*
* @param string $falsePositiveCount
*/
public function setFalsePositiveCount($falsePositiveCount)
{
$this->falsePositiveCount = $falsePositiveCount;
}
/**
* @return string
*/
public function getFalsePositiveCount()
{
return $this->falsePositiveCount;
}
/**
* False Positive Rate for the given confidence threshold.
*
* @param float $falsePositiveRate
*/
public function setFalsePositiveRate($falsePositiveRate)
{
$this->falsePositiveRate = $falsePositiveRate;
}
/**
* @return float
*/
public function getFalsePositiveRate()
{
return $this->falsePositiveRate;
}
/**
* The False Positive Rate when only considering the label that has the
* highest prediction score and not below the confidence threshold for each
* example.
*
* @param float $falsePositiveRateAt1
*/
public function setFalsePositiveRateAt1($falsePositiveRateAt1)
{
$this->falsePositiveRateAt1 = $falsePositiveRateAt1;
}
/**
* @return float
*/
public function getFalsePositiveRateAt1()
{
return $this->falsePositiveRateAt1;
}
/**
* Metrics are computed with an assumption that the model always returns at
* most this many predictions (ordered by their score, descendingly), but they
* all still need to meet the confidence_threshold.
*
* @param int $positionThreshold
*/
public function setPositionThreshold($positionThreshold)
{
$this->positionThreshold = $positionThreshold;
}
/**
* @return int
*/
public function getPositionThreshold()
{
return $this->positionThreshold;
}
/**
* Precision for the given confidence threshold.
*
* @param float $precision
*/
public function setPrecision($precision)
{
$this->precision = $precision;
}
/**
* @return float
*/
public function getPrecision()
{
return $this->precision;
}
/**
* The precision when only considering the label that has the highest
* prediction score and not below the confidence threshold for each example.
*
* @param float $precisionAt1
*/
public function setPrecisionAt1($precisionAt1)
{
$this->precisionAt1 = $precisionAt1;
}
/**
* @return float
*/
public function getPrecisionAt1()
{
return $this->precisionAt1;
}
/**
* Recall (true positive rate) for the given confidence threshold.
*
* @param float $recall
*/
public function setRecall($recall)
{
$this->recall = $recall;
}
/**
* @return float
*/
public function getRecall()
{
return $this->recall;
}
/**
* The recall (true positive rate) when only considering the label that has
* the highest prediction score and not below the confidence threshold for
* each example.
*
* @param float $recallAt1
*/
public function setRecallAt1($recallAt1)
{
$this->recallAt1 = $recallAt1;
}
/**
* @return float
*/
public function getRecallAt1()
{
return $this->recallAt1;
}
/**
* The number of labels that were not created by the model, but if they would,
* they would not match a ground truth label.
*
* @param string $trueNegativeCount
*/
public function setTrueNegativeCount($trueNegativeCount)
{
$this->trueNegativeCount = $trueNegativeCount;
}
/**
* @return string
*/
public function getTrueNegativeCount()
{
return $this->trueNegativeCount;
}
/**
* The number of model created labels that match a ground truth label.
*
* @param string $truePositiveCount
*/
public function setTruePositiveCount($truePositiveCount)
{
$this->truePositiveCount = $truePositiveCount;
}
/**
* @return string
*/
public function getTruePositiveCount()
{
return $this->truePositiveCount;
}
}
// Adding a class alias for backwards compatibility with the previous class name.
class_alias(XPSConfidenceMetricsEntry::class, 'Google_Service_CloudNaturalLanguage_XPSConfidenceMetricsEntry');
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