com.google.api.services.bigquery.model.RegressionMetrics Maven / Gradle / Ivy
/*
* 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.
*/
/*
* This code was generated by https://github.com/googleapis/google-api-java-client-services/
* Modify at your own risk.
*/
package com.google.api.services.bigquery.model;
/**
* Evaluation metrics for regression and explicit feedback type matrix factorization models.
*
* This is the Java data model class that specifies how to parse/serialize into the JSON that is
* transmitted over HTTP when working with the BigQuery API. For a detailed explanation see:
* https://developers.google.com/api-client-library/java/google-http-java-client/json
*
*
* @author Google, Inc.
*/
@SuppressWarnings("javadoc")
public final class RegressionMetrics extends com.google.api.client.json.GenericJson {
/**
* Mean absolute error.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.lang.Double meanAbsoluteError;
/**
* Mean squared error.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.lang.Double meanSquaredError;
/**
* Mean squared log error.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.lang.Double meanSquaredLogError;
/**
* Median absolute error.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.lang.Double medianAbsoluteError;
/**
* R^2 score. This corresponds to r2_score in ML.EVALUATE.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.lang.Double rSquared;
/**
* Mean absolute error.
* @return value or {@code null} for none
*/
public java.lang.Double getMeanAbsoluteError() {
return meanAbsoluteError;
}
/**
* Mean absolute error.
* @param meanAbsoluteError meanAbsoluteError or {@code null} for none
*/
public RegressionMetrics setMeanAbsoluteError(java.lang.Double meanAbsoluteError) {
this.meanAbsoluteError = meanAbsoluteError;
return this;
}
/**
* Mean squared error.
* @return value or {@code null} for none
*/
public java.lang.Double getMeanSquaredError() {
return meanSquaredError;
}
/**
* Mean squared error.
* @param meanSquaredError meanSquaredError or {@code null} for none
*/
public RegressionMetrics setMeanSquaredError(java.lang.Double meanSquaredError) {
this.meanSquaredError = meanSquaredError;
return this;
}
/**
* Mean squared log error.
* @return value or {@code null} for none
*/
public java.lang.Double getMeanSquaredLogError() {
return meanSquaredLogError;
}
/**
* Mean squared log error.
* @param meanSquaredLogError meanSquaredLogError or {@code null} for none
*/
public RegressionMetrics setMeanSquaredLogError(java.lang.Double meanSquaredLogError) {
this.meanSquaredLogError = meanSquaredLogError;
return this;
}
/**
* Median absolute error.
* @return value or {@code null} for none
*/
public java.lang.Double getMedianAbsoluteError() {
return medianAbsoluteError;
}
/**
* Median absolute error.
* @param medianAbsoluteError medianAbsoluteError or {@code null} for none
*/
public RegressionMetrics setMedianAbsoluteError(java.lang.Double medianAbsoluteError) {
this.medianAbsoluteError = medianAbsoluteError;
return this;
}
/**
* R^2 score. This corresponds to r2_score in ML.EVALUATE.
* @return value or {@code null} for none
*/
public java.lang.Double getRSquared() {
return rSquared;
}
/**
* R^2 score. This corresponds to r2_score in ML.EVALUATE.
* @param rSquared rSquared or {@code null} for none
*/
public RegressionMetrics setRSquared(java.lang.Double rSquared) {
this.rSquared = rSquared;
return this;
}
@Override
public RegressionMetrics set(String fieldName, Object value) {
return (RegressionMetrics) super.set(fieldName, value);
}
@Override
public RegressionMetrics clone() {
return (RegressionMetrics) super.clone();
}
}