[ML][Inference] adding ensemble model objects

client/rest-high-level/src/main/java/org/elasticsearch/client/ml/inference/MlInferenceNamedXContentProvider.java

@@ -19,6 +19,10 @@
 package org.elasticsearch.client.ml.inference;
 
 import org.elasticsearch.client.ml.inference.trainedmodel.TrainedModel;
+import org.elasticsearch.client.ml.inference.trainedmodel.ensemble.Ensemble;
+import org.elasticsearch.client.ml.inference.trainedmodel.ensemble.OutputAggregator;
+import org.elasticsearch.client.ml.inference.trainedmodel.ensemble.WeightedMode;
+import org.elasticsearch.client.ml.inference.trainedmodel.ensemble.WeightedSum;
 import org.elasticsearch.client.ml.inference.trainedmodel.tree.Tree;
 import org.elasticsearch.client.ml.inference.preprocessing.FrequencyEncoding;
 import org.elasticsearch.client.ml.inference.preprocessing.OneHotEncoding;
@@ -47,6 +51,15 @@ public List<NamedXContentRegistry.Entry> getNamedXContentParsers() {
 
         // Model
         namedXContent.add(new NamedXContentRegistry.Entry(TrainedModel.class, new ParseField(Tree.NAME), Tree::fromXContent));
+        namedXContent.add(new NamedXContentRegistry.Entry(TrainedModel.class, new ParseField(Ensemble.NAME), Ensemble::fromXContent));
+
+        // Aggregating output
+        namedXContent.add(new NamedXContentRegistry.Entry(OutputAggregator.class,
+            new ParseField(WeightedMode.NAME),
+            WeightedMode::fromXContent));
+        namedXContent.add(new NamedXContentRegistry.Entry(OutputAggregator.class,
+            new ParseField(WeightedSum.NAME),
+            WeightedSum::fromXContent));
 
         return namedXContent;
     }

client/rest-high-level/src/main/java/org/elasticsearch/client/ml/inference/trainedmodel/TargetType.java

@@ -0,0 +1,35 @@
+/*
+ * 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.inference.trainedmodel;
+
+import java.util.Locale;
+
+public enum TargetType {
+
+    REGRESSION, CLASSIFICATION;
+
+    public static TargetType fromString(String name) {
+        return valueOf(name.trim().toUpperCase(Locale.ROOT));
+    }
+
+    @Override
+    public String toString() {
+        return name().toLowerCase(Locale.ROOT);
+    }
+}

client/rest-high-level/src/main/java/org/elasticsearch/client/ml/inference/trainedmodel/ensemble/Ensemble.java

@@ -0,0 +1,188 @@
+/*
+ * 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.inference.trainedmodel.ensemble;
+
+import org.elasticsearch.client.ml.inference.NamedXContentObjectHelper;
+import org.elasticsearch.client.ml.inference.trainedmodel.TargetType;
+import org.elasticsearch.client.ml.inference.trainedmodel.TrainedModel;
+import org.elasticsearch.common.Nullable;
+import org.elasticsearch.common.ParseField;
+import org.elasticsearch.common.xcontent.ObjectParser;
+import org.elasticsearch.common.xcontent.ToXContent;
+import org.elasticsearch.common.xcontent.XContentBuilder;
+import org.elasticsearch.common.xcontent.XContentParser;
+
+import java.io.IOException;
+import java.util.Collections;
+import java.util.List;
+import java.util.Objects;
+
+public class Ensemble implements TrainedModel {
+
+    public static final String NAME = "ensemble";
+    public static final ParseField FEATURE_NAMES = new ParseField("feature_names");
+    public static final ParseField TRAINED_MODELS = new ParseField("trained_models");
+    public static final ParseField AGGREGATE_OUTPUT  = new ParseField("aggregate_output");
+    public static final ParseField TARGET_TYPE = new ParseField("target_type");
+    public static final ParseField CLASSIFICATION_LABELS = new ParseField("classification_labels");
+
+    private static final ObjectParser<Builder, Void> PARSER = new ObjectParser<>(
+        NAME,
+        true,
+        Ensemble.Builder::new);
+
+    static {
+        PARSER.declareStringArray(Ensemble.Builder::setFeatureNames, FEATURE_NAMES);
+        PARSER.declareNamedObjects(Ensemble.Builder::setTrainedModels,
+            (p, c, n) ->
+                    p.namedObject(TrainedModel.class, n, null),
+            (ensembleBuilder) -> { /* Noop does not matter client side */ },
+            TRAINED_MODELS);
+        PARSER.declareNamedObjects(Ensemble.Builder::setOutputAggregatorFromParser,
+            (p, c, n) -> p.namedObject(OutputAggregator.class, n, null),
+            (ensembleBuilder) -> { /* Noop does not matter client side */ },
+            AGGREGATE_OUTPUT);
+        PARSER.declareString(Ensemble.Builder::setTargetType, TARGET_TYPE);
+        PARSER.declareStringArray(Ensemble.Builder::setClassificationLabels, CLASSIFICATION_LABELS);
+    }
+
+    public static Ensemble fromXContent(XContentParser parser) {
+        return PARSER.apply(parser, null).build();
+    }
+
+    private final List<String> featureNames;
+    private final List<TrainedModel> models;
+    private final OutputAggregator outputAggregator;
+    private final TargetType targetType;
+    private final List<String> classificationLabels;
+
+    Ensemble(List<String> featureNames,
+             List<TrainedModel> models,
+             @Nullable OutputAggregator outputAggregator,
+             TargetType targetType,
+             @Nullable List<String> classificationLabels) {
+        this.featureNames = featureNames;
+        this.models = models;
+        this.outputAggregator = outputAggregator;
+        this.targetType = targetType;
+        this.classificationLabels = classificationLabels;
+    }
+
+    @Override
+    public List<String> getFeatureNames() {
+        return featureNames;
+    }
+
+    @Override
+    public String getName() {
+        return NAME;
+    }
+
+    @Override
+    public XContentBuilder toXContent(XContentBuilder builder, ToXContent.Params params) throws IOException {
+        builder.startObject();
+        if (featureNames != null) {
+            builder.field(FEATURE_NAMES.getPreferredName(), featureNames);
+        }
+        if (models != null) {
+            NamedXContentObjectHelper.writeNamedObjects(builder, params, true, TRAINED_MODELS.getPreferredName(), models);
+        }
+        if (outputAggregator != null) {
+            NamedXContentObjectHelper.writeNamedObjects(builder,
+                params,
+                false,
+                AGGREGATE_OUTPUT.getPreferredName(),
+                Collections.singletonList(outputAggregator));
+        }
+        if (targetType != null) {
+            builder.field(TARGET_TYPE.getPreferredName(), targetType);
+        }
+        if (classificationLabels != null) {
+            builder.field(CLASSIFICATION_LABELS.getPreferredName(), classificationLabels);
+        }
+        builder.endObject();
+        return builder;
+    }
+
+    @Override
+    public boolean equals(Object o) {
+        if (this == o) return true;
+        if (o == null || getClass() != o.getClass()) return false;
+        Ensemble that = (Ensemble) o;
+        return Objects.equals(featureNames, that.featureNames)
+            && Objects.equals(models, that.models)
+            && Objects.equals(targetType, that.targetType)
+            && Objects.equals(classificationLabels, that.classificationLabels)
+            && Objects.equals(outputAggregator, that.outputAggregator);
+    }
+
+    @Override
+    public int hashCode() {
+        return Objects.hash(featureNames, models, outputAggregator, classificationLabels, targetType);
+    }
+
+    public static Builder builder() {
+        return new Builder();
+    }
+
+    public static class Builder {
+        private List<String> featureNames;
+        private List<TrainedModel> trainedModels;
+        private OutputAggregator outputAggregator;
+        private TargetType targetType;
+        private List<String> classificationLabels;
+
+        public Builder setFeatureNames(List<String> featureNames) {
+            this.featureNames = featureNames;
+            return this;
+        }
+
+        public Builder setTrainedModels(List<TrainedModel> trainedModels) {
+            this.trainedModels = trainedModels;
+            return this;
+        }
+
+        public Builder setOutputAggregator(OutputAggregator outputAggregator) {
+            this.outputAggregator = outputAggregator;
+            return this;
+        }
+
+        public Builder setTargetType(TargetType targetType) {
+            this.targetType = targetType;
+            return this;
+        }
+
+        public Builder setClassificationLabels(List<String> classificationLabels) {
+            this.classificationLabels = classificationLabels;
+            return this;
+        }
+
+        private void setOutputAggregatorFromParser(List<OutputAggregator> outputAggregators) {
+            this.setOutputAggregator(outputAggregators.get(0));
+        }
+
+        private void setTargetType(String targetType) {
+            this.targetType = TargetType.fromString(targetType);
+        }
+
+        public Ensemble build() {
+            return new Ensemble(featureNames, trainedModels, outputAggregator, targetType, classificationLabels);
+        }
+    }
+}

client/rest-high-level/src/main/java/org/elasticsearch/client/ml/inference/trainedmodel/ensemble/OutputAggregator.java

@@ -0,0 +1,28 @@
+/*
+ * 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.inference.trainedmodel.ensemble;
+
+import org.elasticsearch.client.ml.inference.NamedXContentObject;
+
+public interface OutputAggregator extends NamedXContentObject {
+    /**
+     * @return The name of the output aggregator
+     */
+    String getName();
+}

client/rest-high-level/src/main/java/org/elasticsearch/client/ml/inference/trainedmodel/ensemble/WeightedMode.java

@@ -0,0 +1,84 @@
+/*
+ * 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.inference.trainedmodel.ensemble;
+
+
+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;
+
+import java.io.IOException;
+import java.util.List;
+import java.util.Objects;
+
+
+public class WeightedMode implements OutputAggregator {
+
+    public static final String NAME = "weighted_mode";
+    public static final ParseField WEIGHTS = new ParseField("weights");
+
+    @SuppressWarnings("unchecked")
+    private static final ConstructingObjectParser<WeightedMode, Void> PARSER = new ConstructingObjectParser<>(
+        NAME,
+        true,
+        a -> new WeightedMode((List<Double>)a[0]));
+    static {
+        PARSER.declareDoubleArray(ConstructingObjectParser.optionalConstructorArg(), WEIGHTS);
+    }
+
+    public static WeightedMode fromXContent(XContentParser parser) {
+        return PARSER.apply(parser, null);
+    }
+
+    private final List<Double> weights;
+
+    public WeightedMode(List<Double> weights) {
+        this.weights = weights;
+    }
+
+    @Override
+    public String getName() {
+        return NAME;
+    }
+
+    @Override
+    public XContentBuilder toXContent(XContentBuilder builder, ToXContent.Params params) throws IOException {
+        builder.startObject();
+        if (weights != null) {
+            builder.field(WEIGHTS.getPreferredName(), weights);
+        }
+        builder.endObject();
+        return builder;
+    }
+
+    @Override
+    public boolean equals(Object o) {
+        if (this == o) return true;
+        if (o == null || getClass() != o.getClass()) return false;
+        WeightedMode that = (WeightedMode) o;
+        return Objects.equals(weights, that.weights);
+    }
+
+    @Override
+    public int hashCode() {
+        return Objects.hash(weights);
+    }
+}