co.elastic.clients.elasticsearch.ml.evaluate_data_frame.DataframeRegressionSummary Maven / Gradle / Ivy
/*
* 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.evaluate_data_frame;
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.ObjectBuilder;
import co.elastic.clients.util.WithJsonObjectBuilderBase;
import jakarta.json.stream.JsonGenerator;
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.evaluate_data_frame.DataframeRegressionSummary
/**
*
* @see API
* specification
*/
@JsonpDeserializable
public class DataframeRegressionSummary implements JsonpSerializable {
@Nullable
private final DataframeEvaluationValue huber;
@Nullable
private final DataframeEvaluationValue mse;
@Nullable
private final DataframeEvaluationValue msle;
@Nullable
private final DataframeEvaluationValue rSquared;
// ---------------------------------------------------------------------------------------------
private DataframeRegressionSummary(Builder builder) {
this.huber = builder.huber;
this.mse = builder.mse;
this.msle = builder.msle;
this.rSquared = builder.rSquared;
}
public static DataframeRegressionSummary of(Function> fn) {
return fn.apply(new Builder()).build();
}
/**
* Pseudo Huber loss function.
*
* API name: {@code huber}
*/
@Nullable
public final DataframeEvaluationValue huber() {
return this.huber;
}
/**
* Average squared difference between the predicted values and the actual
* (ground truth) value.
*
* API name: {@code mse}
*/
@Nullable
public final DataframeEvaluationValue 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 DataframeEvaluationValue msle() {
return this.msle;
}
/**
* Proportion of the variance in the dependent variable that is predictable from
* the independent variables.
*
* API name: {@code r_squared}
*/
@Nullable
public final DataframeEvaluationValue 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 (this.huber != null) {
generator.writeKey("huber");
this.huber.serialize(generator, mapper);
}
if (this.mse != null) {
generator.writeKey("mse");
this.mse.serialize(generator, mapper);
}
if (this.msle != null) {
generator.writeKey("msle");
this.msle.serialize(generator, mapper);
}
if (this.rSquared != null) {
generator.writeKey("r_squared");
this.rSquared.serialize(generator, mapper);
}
}
@Override
public String toString() {
return JsonpUtils.toString(this);
}
// ---------------------------------------------------------------------------------------------
/**
* Builder for {@link DataframeRegressionSummary}.
*/
public static class Builder extends WithJsonObjectBuilderBase
implements
ObjectBuilder {
@Nullable
private DataframeEvaluationValue huber;
@Nullable
private DataframeEvaluationValue mse;
@Nullable
private DataframeEvaluationValue msle;
@Nullable
private DataframeEvaluationValue rSquared;
/**
* Pseudo Huber loss function.
*
* API name: {@code huber}
*/
public final Builder huber(@Nullable DataframeEvaluationValue 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 DataframeEvaluationValue.Builder()).build());
}
/**
* Average squared difference between the predicted values and the actual
* (ground truth) value.
*
* API name: {@code mse}
*/
public final Builder mse(@Nullable DataframeEvaluationValue value) {
this.mse = value;
return this;
}
/**
* Average squared difference between the predicted values and the actual
* (ground truth) value.
*
* API name: {@code mse}
*/
public final Builder mse(
Function> fn) {
return this.mse(fn.apply(new DataframeEvaluationValue.Builder()).build());
}
/**
* 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 DataframeEvaluationValue 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 DataframeEvaluationValue.Builder()).build());
}
/**
* Proportion of the variance in the dependent variable that is predictable from
* the independent variables.
*
* API name: {@code r_squared}
*/
public final Builder rSquared(@Nullable DataframeEvaluationValue value) {
this.rSquared = value;
return this;
}
/**
* Proportion of the variance in the dependent variable that is predictable from
* the independent variables.
*
* API name: {@code r_squared}
*/
public final Builder rSquared(
Function> fn) {
return this.rSquared(fn.apply(new DataframeEvaluationValue.Builder()).build());
}
@Override
protected Builder self() {
return this;
}
/**
* Builds a {@link DataframeRegressionSummary}.
*
* @throws NullPointerException
* if some of the required fields are null.
*/
public DataframeRegressionSummary build() {
_checkSingleUse();
return new DataframeRegressionSummary(this);
}
}
// ---------------------------------------------------------------------------------------------
/**
* Json deserializer for {@link DataframeRegressionSummary}
*/
public static final JsonpDeserializer _DESERIALIZER = ObjectBuilderDeserializer
.lazy(Builder::new, DataframeRegressionSummary::setupDataframeRegressionSummaryDeserializer);
protected static void setupDataframeRegressionSummaryDeserializer(
ObjectDeserializer op) {
op.add(Builder::huber, DataframeEvaluationValue._DESERIALIZER, "huber");
op.add(Builder::mse, DataframeEvaluationValue._DESERIALIZER, "mse");
op.add(Builder::msle, DataframeEvaluationValue._DESERIALIZER, "msle");
op.add(Builder::rSquared, DataframeEvaluationValue._DESERIALIZER, "r_squared");
}
}