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[ML] Adds support for regression.mean_squared_error to eval API (elas…
…tic#44140) * [ML] Adds support for regression.mean_squared_error to eval API * addressing PR comments * fixing tests
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129 changes: 129 additions & 0 deletions
129
...a/org/elasticsearch/client/ml/dataframe/evaluation/regression/MeanSquaredErrorMetric.java
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,129 @@ | ||
| /* | ||
| * Licensed to Elasticsearch under one or more contributor | ||
| * license agreements. See the NOTICE file distributed with | ||
| * this work for additional information regarding copyright | ||
| * ownership. Elasticsearch licenses this file to you 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. | ||
| */ | ||
| package org.elasticsearch.client.ml.dataframe.evaluation.regression; | ||
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| import org.elasticsearch.client.ml.dataframe.evaluation.EvaluationMetric; | ||
| import org.elasticsearch.common.ParseField; | ||
| import org.elasticsearch.common.xcontent.ConstructingObjectParser; | ||
| import org.elasticsearch.common.xcontent.ObjectParser; | ||
| import org.elasticsearch.common.xcontent.ToXContent; | ||
| import org.elasticsearch.common.xcontent.XContentBuilder; | ||
| import org.elasticsearch.common.xcontent.XContentParser; | ||
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|
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| import java.io.IOException; | ||
| import java.util.Objects; | ||
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| import static org.elasticsearch.common.xcontent.ConstructingObjectParser.constructorArg; | ||
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| /** | ||
| * Calculates the mean squared error between two known numerical fields. | ||
| * | ||
| * equation: mse = 1/n * Σ(y - y´)^2 | ||
| */ | ||
| public class MeanSquaredErrorMetric implements EvaluationMetric { | ||
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| public static final String NAME = "mean_squared_error"; | ||
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| private static final ObjectParser<MeanSquaredErrorMetric, Void> PARSER = | ||
| new ObjectParser<>("mean_squared_error", true, MeanSquaredErrorMetric::new); | ||
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| public static MeanSquaredErrorMetric fromXContent(XContentParser parser) { | ||
| return PARSER.apply(parser, null); | ||
| } | ||
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| public MeanSquaredErrorMetric() { | ||
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| } | ||
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| @Override | ||
| public XContentBuilder toXContent(XContentBuilder builder, ToXContent.Params params) throws IOException { | ||
| builder.startObject(); | ||
| builder.endObject(); | ||
| return builder; | ||
| } | ||
|
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| @Override | ||
| public boolean equals(Object o) { | ||
| if (this == o) return true; | ||
| if (o == null || getClass() != o.getClass()) return false; | ||
| return true; | ||
| } | ||
|
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| @Override | ||
| public int hashCode() { | ||
| // create static hash code from name as there are currently no unique fields per class instance | ||
| return Objects.hashCode(NAME); | ||
| } | ||
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| @Override | ||
| public String getName() { | ||
| return NAME; | ||
| } | ||
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| public static class Result implements EvaluationMetric.Result { | ||
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| public static final ParseField ERROR = new ParseField("error"); | ||
| private final double error; | ||
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| public static Result fromXContent(XContentParser parser) { | ||
| return PARSER.apply(parser, null); | ||
| } | ||
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| private static final ConstructingObjectParser<Result, Void> PARSER = | ||
| new ConstructingObjectParser<>("mean_squared_error_result", true, args -> new Result((double) args[0])); | ||
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| static { | ||
| PARSER.declareDouble(constructorArg(), ERROR); | ||
| } | ||
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| public Result(double error) { | ||
| this.error = error; | ||
| } | ||
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| @Override | ||
| public XContentBuilder toXContent(XContentBuilder builder, ToXContent.Params params) throws IOException { | ||
| builder.startObject(); | ||
| builder.field(ERROR.getPreferredName(), error); | ||
| builder.endObject(); | ||
| return builder; | ||
| } | ||
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| public double getError() { | ||
| return error; | ||
| } | ||
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| @Override | ||
| public String getMetricName() { | ||
| return NAME; | ||
| } | ||
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| @Override | ||
| public boolean equals(Object o) { | ||
| if (this == o) return true; | ||
| if (o == null || getClass() != o.getClass()) return false; | ||
| Result that = (Result) o; | ||
| return Objects.equals(that.error, this.error); | ||
| } | ||
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| @Override | ||
| public int hashCode() { | ||
| return Objects.hash(error); | ||
| } | ||
| } | ||
| } |
129 changes: 129 additions & 0 deletions
129
...src/main/java/org/elasticsearch/client/ml/dataframe/evaluation/regression/Regression.java
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,129 @@ | ||
| /* | ||
| * Licensed to Elasticsearch under one or more contributor | ||
| * license agreements. See the NOTICE file distributed with | ||
| * this work for additional information regarding copyright | ||
| * ownership. Elasticsearch licenses this file to you 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. | ||
| */ | ||
| package org.elasticsearch.client.ml.dataframe.evaluation.regression; | ||
|
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| import org.elasticsearch.client.ml.dataframe.evaluation.Evaluation; | ||
| import org.elasticsearch.client.ml.dataframe.evaluation.EvaluationMetric; | ||
| import org.elasticsearch.common.Nullable; | ||
| import org.elasticsearch.common.ParseField; | ||
| import org.elasticsearch.common.xcontent.ConstructingObjectParser; | ||
| import org.elasticsearch.common.xcontent.ToXContent; | ||
| import org.elasticsearch.common.xcontent.XContentBuilder; | ||
| import org.elasticsearch.common.xcontent.XContentParser; | ||
|
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| import java.io.IOException; | ||
| import java.util.Arrays; | ||
| import java.util.List; | ||
| import java.util.Objects; | ||
|
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| /** | ||
| * Evaluation of regression results. | ||
| */ | ||
| public class Regression implements Evaluation { | ||
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| public static final String NAME = "regression"; | ||
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| private static final ParseField ACTUAL_FIELD = new ParseField("actual_field"); | ||
| private static final ParseField PREDICTED_FIELD = new ParseField("predicted_field"); | ||
| private static final ParseField METRICS = new ParseField("metrics"); | ||
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| @SuppressWarnings("unchecked") | ||
| public static final ConstructingObjectParser<Regression, Void> PARSER = new ConstructingObjectParser<>( | ||
| NAME, true, a -> new Regression((String) a[0], (String) a[1], (List<EvaluationMetric>) a[2])); | ||
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| static { | ||
| PARSER.declareString(ConstructingObjectParser.constructorArg(), ACTUAL_FIELD); | ||
| PARSER.declareString(ConstructingObjectParser.constructorArg(), PREDICTED_FIELD); | ||
| PARSER.declareNamedObjects(ConstructingObjectParser.optionalConstructorArg(), | ||
| (p, c, n) -> p.namedObject(EvaluationMetric.class, n, c), METRICS); | ||
| } | ||
|
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| public static Regression fromXContent(XContentParser parser) { | ||
| return PARSER.apply(parser, null); | ||
| } | ||
|
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| /** | ||
| * The field containing the actual value | ||
| * The value of this field is assumed to be numeric | ||
| */ | ||
| private final String actualField; | ||
|
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| /** | ||
| * The field containing the predicted value | ||
| * The value of this field is assumed to be numeric | ||
| */ | ||
| private final String predictedField; | ||
|
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| /** | ||
| * The list of metrics to calculate | ||
| */ | ||
| private final List<EvaluationMetric> metrics; | ||
|
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| public Regression(String actualField, String predictedField) { | ||
| this(actualField, predictedField, (List<EvaluationMetric>)null); | ||
| } | ||
|
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| public Regression(String actualField, String predictedField, EvaluationMetric... metrics) { | ||
| this(actualField, predictedField, Arrays.asList(metrics)); | ||
| } | ||
|
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| public Regression(String actualField, String predictedField, @Nullable List<EvaluationMetric> metrics) { | ||
| this.actualField = actualField; | ||
| this.predictedField = predictedField; | ||
| this.metrics = metrics; | ||
| } | ||
|
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| @Override | ||
| public String getName() { | ||
| return NAME; | ||
| } | ||
|
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| @Override | ||
| public XContentBuilder toXContent(XContentBuilder builder, ToXContent.Params params) throws IOException { | ||
| builder.startObject(); | ||
| builder.field(ACTUAL_FIELD.getPreferredName(), actualField); | ||
| builder.field(PREDICTED_FIELD.getPreferredName(), predictedField); | ||
|
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| if (metrics != null) { | ||
| builder.startObject(METRICS.getPreferredName()); | ||
| for (EvaluationMetric metric : metrics) { | ||
| builder.field(metric.getName(), metric); | ||
| } | ||
| builder.endObject(); | ||
| } | ||
|
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| builder.endObject(); | ||
| return builder; | ||
| } | ||
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| @Override | ||
| public boolean equals(Object o) { | ||
| if (this == o) return true; | ||
| if (o == null || getClass() != o.getClass()) return false; | ||
| Regression that = (Regression) o; | ||
| return Objects.equals(that.actualField, this.actualField) | ||
| && Objects.equals(that.predictedField, this.predictedField) | ||
| && Objects.equals(that.metrics, this.metrics); | ||
| } | ||
|
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| @Override | ||
| public int hashCode() { | ||
| return Objects.hash(actualField, predictedField, metrics); | ||
| } | ||
| } |
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