📄 Source: XPSTablesModelColumnInfo.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 XPSTablesModelColumnInfo extends \Google\Model
{
/**
* The ID of the column.
*
* @var int
*/
public $columnId;
/**
* When given as part of a Model: Measurement of how much model predictions
* correctness on the TEST data depend on values in this column. A value
* between 0 and 1, higher means higher influence. These values are normalized
* - for all input feature columns of a given model they add to 1. When given
* back by Predict or Batch Predict: Measurement of how impactful for the
* prediction returned for the given row the value in this column was.
* Specifically, the feature importance specifies the marginal contribution
* that the feature made to the prediction score compared to the baseline
* score. These values are computed using the Sampled Shapley method.
*
* @var float
*/
public $featureImportance;
/**
* The ID of the column.
*
* @param int $columnId
*/
public function setColumnId($columnId)
{
$this->columnId = $columnId;
}
/**
* @return int
*/
public function getColumnId()
{
return $this->columnId;
}
/**
* When given as part of a Model: Measurement of how much model predictions
* correctness on the TEST data depend on values in this column. A value
* between 0 and 1, higher means higher influence. These values are normalized
* - for all input feature columns of a given model they add to 1. When given
* back by Predict or Batch Predict: Measurement of how impactful for the
* prediction returned for the given row the value in this column was.
* Specifically, the feature importance specifies the marginal contribution
* that the feature made to the prediction score compared to the baseline
* score. These values are computed using the Sampled Shapley method.
*
* @param float $featureImportance
*/
public function setFeatureImportance($featureImportance)
{
$this->featureImportance = $featureImportance;
}
/**
* @return float
*/
public function getFeatureImportance()
{
return $this->featureImportance;
}
}
// Adding a class alias for backwards compatibility with the previous class name.
class_alias(XPSTablesModelColumnInfo::class, 'Google_Service_CloudNaturalLanguage_XPSTablesModelColumnInfo');
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