co.elastic.clients.elasticsearch.ml.DataframeEvaluationRegressionMetrics Maven / Gradle / Ivy
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/*
* Licensed to Elasticsearch B.V. under one or more contributor
* license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright
* ownership. Elasticsearch B.V. 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 co.elastic.clients.elasticsearch.ml;
import co.elastic.clients.json.JsonData;
import co.elastic.clients.json.JsonpDeserializable;
import co.elastic.clients.json.JsonpDeserializer;
import co.elastic.clients.json.JsonpMapper;
import co.elastic.clients.json.JsonpSerializable;
import co.elastic.clients.json.JsonpUtils;
import co.elastic.clients.json.ObjectBuilderDeserializer;
import co.elastic.clients.json.ObjectDeserializer;
import co.elastic.clients.util.ApiTypeHelper;
import co.elastic.clients.util.ObjectBuilder;
import co.elastic.clients.util.WithJsonObjectBuilderBase;
import jakarta.json.stream.JsonGenerator;
import java.lang.String;
import java.util.Map;
import java.util.Objects;
import java.util.function.Function;
import javax.annotation.Nullable;
//----------------------------------------------------------------
// THIS CODE IS GENERATED. MANUAL EDITS WILL BE LOST.
//----------------------------------------------------------------
//
// This code is generated from the Elasticsearch API specification
// at https://github.com/elastic/elasticsearch-specification
//
// Manual updates to this file will be lost when the code is
// re-generated.
//
// If you find a property that is missing or wrongly typed, please
// open an issue or a PR on the API specification repository.
//
//----------------------------------------------------------------
// typedef: ml._types.DataframeEvaluationRegressionMetrics
/**
*
* @see API
* specification
*/
@JsonpDeserializable
public class DataframeEvaluationRegressionMetrics implements JsonpSerializable {
private final Map mse;
@Nullable
private final DataframeEvaluationRegressionMetricsMsle msle;
@Nullable
private final DataframeEvaluationRegressionMetricsHuber huber;
private final Map rSquared;
// ---------------------------------------------------------------------------------------------
private DataframeEvaluationRegressionMetrics(Builder builder) {
this.mse = ApiTypeHelper.unmodifiable(builder.mse);
this.msle = builder.msle;
this.huber = builder.huber;
this.rSquared = ApiTypeHelper.unmodifiable(builder.rSquared);
}
public static DataframeEvaluationRegressionMetrics of(
Function> fn) {
return fn.apply(new Builder()).build();
}
/**
* Average squared difference between the predicted values and the actual
* (ground truth) value. For more information, read this wiki article.
*
* API name: {@code mse}
*/
public final Map mse() {
return this.mse;
}
/**
* Average squared difference between the logarithm of the predicted values and
* the logarithm of the actual (ground truth) value.
*
* API name: {@code msle}
*/
@Nullable
public final DataframeEvaluationRegressionMetricsMsle msle() {
return this.msle;
}
/**
* Pseudo Huber loss function.
*
* API name: {@code huber}
*/
@Nullable
public final DataframeEvaluationRegressionMetricsHuber huber() {
return this.huber;
}
/**
* Proportion of the variance in the dependent variable that is predictable from
* the independent variables.
*
* API name: {@code r_squared}
*/
public final Map rSquared() {
return this.rSquared;
}
/**
* Serialize this object to JSON.
*/
public void serialize(JsonGenerator generator, JsonpMapper mapper) {
generator.writeStartObject();
serializeInternal(generator, mapper);
generator.writeEnd();
}
protected void serializeInternal(JsonGenerator generator, JsonpMapper mapper) {
if (ApiTypeHelper.isDefined(this.mse)) {
generator.writeKey("mse");
generator.writeStartObject();
for (Map.Entry item0 : this.mse.entrySet()) {
generator.writeKey(item0.getKey());
item0.getValue().serialize(generator, mapper);
}
generator.writeEnd();
}
if (this.msle != null) {
generator.writeKey("msle");
this.msle.serialize(generator, mapper);
}
if (this.huber != null) {
generator.writeKey("huber");
this.huber.serialize(generator, mapper);
}
if (ApiTypeHelper.isDefined(this.rSquared)) {
generator.writeKey("r_squared");
generator.writeStartObject();
for (Map.Entry item0 : this.rSquared.entrySet()) {
generator.writeKey(item0.getKey());
item0.getValue().serialize(generator, mapper);
}
generator.writeEnd();
}
}
@Override
public String toString() {
return JsonpUtils.toString(this);
}
// ---------------------------------------------------------------------------------------------
/**
* Builder for {@link DataframeEvaluationRegressionMetrics}.
*/
public static class Builder extends WithJsonObjectBuilderBase
implements
ObjectBuilder {
@Nullable
private Map mse;
@Nullable
private DataframeEvaluationRegressionMetricsMsle msle;
@Nullable
private DataframeEvaluationRegressionMetricsHuber huber;
@Nullable
private Map rSquared;
/**
* Average squared difference between the predicted values and the actual
* (ground truth) value. For more information, read this wiki article.
*
* API name: {@code mse}
*
* Adds all entries of map to mse.
*/
public final Builder mse(Map map) {
this.mse = _mapPutAll(this.mse, map);
return this;
}
/**
* Average squared difference between the predicted values and the actual
* (ground truth) value. For more information, read this wiki article.
*
* API name: {@code mse}
*
* Adds an entry to mse.
*/
public final Builder mse(String key, JsonData value) {
this.mse = _mapPut(this.mse, key, value);
return this;
}
/**
* Average squared difference between the logarithm of the predicted values and
* the logarithm of the actual (ground truth) value.
*
* API name: {@code msle}
*/
public final Builder msle(@Nullable DataframeEvaluationRegressionMetricsMsle value) {
this.msle = value;
return this;
}
/**
* Average squared difference between the logarithm of the predicted values and
* the logarithm of the actual (ground truth) value.
*
* API name: {@code msle}
*/
public final Builder msle(
Function> fn) {
return this.msle(fn.apply(new DataframeEvaluationRegressionMetricsMsle.Builder()).build());
}
/**
* Pseudo Huber loss function.
*
* API name: {@code huber}
*/
public final Builder huber(@Nullable DataframeEvaluationRegressionMetricsHuber value) {
this.huber = value;
return this;
}
/**
* Pseudo Huber loss function.
*
* API name: {@code huber}
*/
public final Builder huber(
Function> fn) {
return this.huber(fn.apply(new DataframeEvaluationRegressionMetricsHuber.Builder()).build());
}
/**
* Proportion of the variance in the dependent variable that is predictable from
* the independent variables.
*
* API name: {@code r_squared}
*
* Adds all entries of map to rSquared.
*/
public final Builder rSquared(Map map) {
this.rSquared = _mapPutAll(this.rSquared, map);
return this;
}
/**
* Proportion of the variance in the dependent variable that is predictable from
* the independent variables.
*
* API name: {@code r_squared}
*
* Adds an entry to rSquared.
*/
public final Builder rSquared(String key, JsonData value) {
this.rSquared = _mapPut(this.rSquared, key, value);
return this;
}
@Override
protected Builder self() {
return this;
}
/**
* Builds a {@link DataframeEvaluationRegressionMetrics}.
*
* @throws NullPointerException
* if some of the required fields are null.
*/
public DataframeEvaluationRegressionMetrics build() {
_checkSingleUse();
return new DataframeEvaluationRegressionMetrics(this);
}
}
// ---------------------------------------------------------------------------------------------
/**
* Json deserializer for {@link DataframeEvaluationRegressionMetrics}
*/
public static final JsonpDeserializer _DESERIALIZER = ObjectBuilderDeserializer
.lazy(Builder::new,
DataframeEvaluationRegressionMetrics::setupDataframeEvaluationRegressionMetricsDeserializer);
protected static void setupDataframeEvaluationRegressionMetricsDeserializer(
ObjectDeserializer op) {
op.add(Builder::mse, JsonpDeserializer.stringMapDeserializer(JsonData._DESERIALIZER), "mse");
op.add(Builder::msle, DataframeEvaluationRegressionMetricsMsle._DESERIALIZER, "msle");
op.add(Builder::huber, DataframeEvaluationRegressionMetricsHuber._DESERIALIZER, "huber");
op.add(Builder::rSquared, JsonpDeserializer.stringMapDeserializer(JsonData._DESERIALIZER), "r_squared");
}
}