📄 Source: RankingMetrics.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\Bigquery;
class RankingMetrics extends \Google\Model
{
/**
* Determines the goodness of a ranking by computing the percentile rank from
* the predicted confidence and dividing it by the original rank.
*
* @var
*/
public $averageRank;
/**
* Calculates a precision per user for all the items by ranking them and then
* averages all the precisions across all the users.
*
* @var
*/
public $meanAveragePrecision;
/**
* Similar to the mean squared error computed in regression and explicit
* recommendation models except instead of computing the rating directly, the
* output from evaluate is computed against a preference which is 1 or 0
* depending on if the rating exists or not.
*
* @var
*/
public $meanSquaredError;
/**
* A metric to determine the goodness of a ranking calculated from the
* predicted confidence by comparing it to an ideal rank measured by the
* original ratings.
*
* @var
*/
public $normalizedDiscountedCumulativeGain;
public function setAverageRank($averageRank)
{
$this->averageRank = $averageRank;
}
public function getAverageRank()
{
return $this->averageRank;
}
public function setMeanAveragePrecision($meanAveragePrecision)
{
$this->meanAveragePrecision = $meanAveragePrecision;
}
public function getMeanAveragePrecision()
{
return $this->meanAveragePrecision;
}
public function setMeanSquaredError($meanSquaredError)
{
$this->meanSquaredError = $meanSquaredError;
}
public function getMeanSquaredError()
{
return $this->meanSquaredError;
}
public function setNormalizedDiscountedCumulativeGain($normalizedDiscountedCumulativeGain)
{
$this->normalizedDiscountedCumulativeGain = $normalizedDiscountedCumulativeGain;
}
public function getNormalizedDiscountedCumulativeGain()
{
return $this->normalizedDiscountedCumulativeGain;
}
}
// Adding a class alias for backwards compatibility with the previous class name.
class_alias(RankingMetrics::class, 'Google_Service_Bigquery_RankingMetrics');
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