co.elastic.clients.elasticsearch.ml.DataframeEvaluationOutlierDetection Maven / Gradle / Ivy
Show all versions of elasticsearch-java Show documentation
/*
* 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.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.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.DataframeEvaluationOutlierDetection
/**
*
* @see API
* specification
*/
@JsonpDeserializable
public class DataframeEvaluationOutlierDetection implements DataframeEvaluationVariant, JsonpSerializable {
private final String actualField;
private final String predictedProbabilityField;
@Nullable
private final DataframeEvaluationOutlierDetectionMetrics metrics;
// ---------------------------------------------------------------------------------------------
private DataframeEvaluationOutlierDetection(Builder builder) {
this.actualField = ApiTypeHelper.requireNonNull(builder.actualField, this, "actualField");
this.predictedProbabilityField = ApiTypeHelper.requireNonNull(builder.predictedProbabilityField, this,
"predictedProbabilityField");
this.metrics = builder.metrics;
}
public static DataframeEvaluationOutlierDetection of(
Function> fn) {
return fn.apply(new Builder()).build();
}
/**
* DataframeEvaluation variant kind.
*/
@Override
public DataframeEvaluation.Kind _dataframeEvaluationKind() {
return DataframeEvaluation.Kind.OutlierDetection;
}
/**
* Required - The field of the index which contains the ground truth. The data
* type of this field can be boolean or integer. If the data type is integer,
* the value has to be either 0 (false) or 1 (true).
*
* API name: {@code actual_field}
*/
public final String actualField() {
return this.actualField;
}
/**
* Required - The field of the index that defines the probability of whether the
* item belongs to the class in question or not. It’s the field that contains
* the results of the analysis.
*
* API name: {@code predicted_probability_field}
*/
public final String predictedProbabilityField() {
return this.predictedProbabilityField;
}
/**
* Specifies the metrics that are used for the evaluation.
*
* API name: {@code metrics}
*/
@Nullable
public final DataframeEvaluationOutlierDetectionMetrics metrics() {
return this.metrics;
}
/**
* 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) {
generator.writeKey("actual_field");
generator.write(this.actualField);
generator.writeKey("predicted_probability_field");
generator.write(this.predictedProbabilityField);
if (this.metrics != null) {
generator.writeKey("metrics");
this.metrics.serialize(generator, mapper);
}
}
@Override
public String toString() {
return JsonpUtils.toString(this);
}
// ---------------------------------------------------------------------------------------------
/**
* Builder for {@link DataframeEvaluationOutlierDetection}.
*/
public static class Builder extends WithJsonObjectBuilderBase
implements
ObjectBuilder {
private String actualField;
private String predictedProbabilityField;
@Nullable
private DataframeEvaluationOutlierDetectionMetrics metrics;
/**
* Required - The field of the index which contains the ground truth. The data
* type of this field can be boolean or integer. If the data type is integer,
* the value has to be either 0 (false) or 1 (true).
*
* API name: {@code actual_field}
*/
public final Builder actualField(String value) {
this.actualField = value;
return this;
}
/**
* Required - The field of the index that defines the probability of whether the
* item belongs to the class in question or not. It’s the field that contains
* the results of the analysis.
*
* API name: {@code predicted_probability_field}
*/
public final Builder predictedProbabilityField(String value) {
this.predictedProbabilityField = value;
return this;
}
/**
* Specifies the metrics that are used for the evaluation.
*
* API name: {@code metrics}
*/
public final Builder metrics(@Nullable DataframeEvaluationOutlierDetectionMetrics value) {
this.metrics = value;
return this;
}
/**
* Specifies the metrics that are used for the evaluation.
*
* API name: {@code metrics}
*/
public final Builder metrics(
Function> fn) {
return this.metrics(fn.apply(new DataframeEvaluationOutlierDetectionMetrics.Builder()).build());
}
@Override
protected Builder self() {
return this;
}
/**
* Builds a {@link DataframeEvaluationOutlierDetection}.
*
* @throws NullPointerException
* if some of the required fields are null.
*/
public DataframeEvaluationOutlierDetection build() {
_checkSingleUse();
return new DataframeEvaluationOutlierDetection(this);
}
}
// ---------------------------------------------------------------------------------------------
/**
* Json deserializer for {@link DataframeEvaluationOutlierDetection}
*/
public static final JsonpDeserializer _DESERIALIZER = ObjectBuilderDeserializer
.lazy(Builder::new,
DataframeEvaluationOutlierDetection::setupDataframeEvaluationOutlierDetectionDeserializer);
protected static void setupDataframeEvaluationOutlierDetectionDeserializer(
ObjectDeserializer op) {
op.add(Builder::actualField, JsonpDeserializer.stringDeserializer(), "actual_field");
op.add(Builder::predictedProbabilityField, JsonpDeserializer.stringDeserializer(),
"predicted_probability_field");
op.add(Builder::metrics, DataframeEvaluationOutlierDetectionMetrics._DESERIALIZER, "metrics");
}
}