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/*
 * 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 of a model. These are either computed on all training data or just the eval
 * data based on whether eval data was used during training. These are not present for imported
 * 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 EvaluationMetrics extends com.google.api.client.json.GenericJson { /** * Populated for ARIMA models. * The value may be {@code null}. */ @com.google.api.client.util.Key private ArimaForecastingMetrics arimaForecastingMetrics; /** * Populated for binary classification/classifier models. * The value may be {@code null}. */ @com.google.api.client.util.Key private BinaryClassificationMetrics binaryClassificationMetrics; /** * Populated for clustering models. * The value may be {@code null}. */ @com.google.api.client.util.Key private ClusteringMetrics clusteringMetrics; /** * Evaluation metrics when the model is a dimensionality reduction model, which currently includes * PCA. * The value may be {@code null}. */ @com.google.api.client.util.Key private DimensionalityReductionMetrics dimensionalityReductionMetrics; /** * Populated for multi-class classification/classifier models. * The value may be {@code null}. */ @com.google.api.client.util.Key private MultiClassClassificationMetrics multiClassClassificationMetrics; /** * Populated for implicit feedback type matrix factorization models. * The value may be {@code null}. */ @com.google.api.client.util.Key private RankingMetrics rankingMetrics; /** * Populated for regression models and explicit feedback type matrix factorization models. * The value may be {@code null}. */ @com.google.api.client.util.Key private RegressionMetrics regressionMetrics; /** * Populated for ARIMA models. * @return value or {@code null} for none */ public ArimaForecastingMetrics getArimaForecastingMetrics() { return arimaForecastingMetrics; } /** * Populated for ARIMA models. * @param arimaForecastingMetrics arimaForecastingMetrics or {@code null} for none */ public EvaluationMetrics setArimaForecastingMetrics(ArimaForecastingMetrics arimaForecastingMetrics) { this.arimaForecastingMetrics = arimaForecastingMetrics; return this; } /** * Populated for binary classification/classifier models. * @return value or {@code null} for none */ public BinaryClassificationMetrics getBinaryClassificationMetrics() { return binaryClassificationMetrics; } /** * Populated for binary classification/classifier models. * @param binaryClassificationMetrics binaryClassificationMetrics or {@code null} for none */ public EvaluationMetrics setBinaryClassificationMetrics(BinaryClassificationMetrics binaryClassificationMetrics) { this.binaryClassificationMetrics = binaryClassificationMetrics; return this; } /** * Populated for clustering models. * @return value or {@code null} for none */ public ClusteringMetrics getClusteringMetrics() { return clusteringMetrics; } /** * Populated for clustering models. * @param clusteringMetrics clusteringMetrics or {@code null} for none */ public EvaluationMetrics setClusteringMetrics(ClusteringMetrics clusteringMetrics) { this.clusteringMetrics = clusteringMetrics; return this; } /** * Evaluation metrics when the model is a dimensionality reduction model, which currently includes * PCA. * @return value or {@code null} for none */ public DimensionalityReductionMetrics getDimensionalityReductionMetrics() { return dimensionalityReductionMetrics; } /** * Evaluation metrics when the model is a dimensionality reduction model, which currently includes * PCA. * @param dimensionalityReductionMetrics dimensionalityReductionMetrics or {@code null} for none */ public EvaluationMetrics setDimensionalityReductionMetrics(DimensionalityReductionMetrics dimensionalityReductionMetrics) { this.dimensionalityReductionMetrics = dimensionalityReductionMetrics; return this; } /** * Populated for multi-class classification/classifier models. * @return value or {@code null} for none */ public MultiClassClassificationMetrics getMultiClassClassificationMetrics() { return multiClassClassificationMetrics; } /** * Populated for multi-class classification/classifier models. * @param multiClassClassificationMetrics multiClassClassificationMetrics or {@code null} for none */ public EvaluationMetrics setMultiClassClassificationMetrics(MultiClassClassificationMetrics multiClassClassificationMetrics) { this.multiClassClassificationMetrics = multiClassClassificationMetrics; return this; } /** * Populated for implicit feedback type matrix factorization models. * @return value or {@code null} for none */ public RankingMetrics getRankingMetrics() { return rankingMetrics; } /** * Populated for implicit feedback type matrix factorization models. * @param rankingMetrics rankingMetrics or {@code null} for none */ public EvaluationMetrics setRankingMetrics(RankingMetrics rankingMetrics) { this.rankingMetrics = rankingMetrics; return this; } /** * Populated for regression models and explicit feedback type matrix factorization models. * @return value or {@code null} for none */ public RegressionMetrics getRegressionMetrics() { return regressionMetrics; } /** * Populated for regression models and explicit feedback type matrix factorization models. * @param regressionMetrics regressionMetrics or {@code null} for none */ public EvaluationMetrics setRegressionMetrics(RegressionMetrics regressionMetrics) { this.regressionMetrics = regressionMetrics; return this; } @Override public EvaluationMetrics set(String fieldName, Object value) { return (EvaluationMetrics) super.set(fieldName, value); } @Override public EvaluationMetrics clone() { return (EvaluationMetrics) super.clone(); } }




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