[ML][Inference] adds logistic_regression output aggregator

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

@@ -20,6 +20,7 @@
 
 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.LogisticRegression;
 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;
@@ -60,6 +61,9 @@ public List<NamedXContentRegistry.Entry> getNamedXContentParsers() {
         namedXContent.add(new NamedXContentRegistry.Entry(OutputAggregator.class,
             new ParseField(WeightedSum.NAME),
             WeightedSum::fromXContent));
+        namedXContent.add(new NamedXContentRegistry.Entry(OutputAggregator.class,
+            new ParseField(LogisticRegression.NAME),
+            LogisticRegression::fromXContent));
 
         return namedXContent;
     }

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

@@ -0,0 +1,83 @@
+/*
+ * 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.XContentBuilder;
+import org.elasticsearch.common.xcontent.XContentParser;
+
+import java.io.IOException;
+import java.util.List;
+import java.util.Objects;
+
+
+public class LogisticRegression implements OutputAggregator {
+
+    public static final String NAME = "logistic_regression";
+    public static final ParseField WEIGHTS = new ParseField("weights");
+
+    @SuppressWarnings("unchecked")
+    private static final ConstructingObjectParser<LogisticRegression, Void> PARSER = new ConstructingObjectParser<>(
+        NAME,
+        true,
+        a -> new LogisticRegression((List<Double>)a[0]));
+    static {
+        PARSER.declareDoubleArray(ConstructingObjectParser.optionalConstructorArg(), WEIGHTS);
+    }
+
+    public static LogisticRegression fromXContent(XContentParser parser) {
+        return PARSER.apply(parser, null);
+    }
+
+    private final List<Double> weights;
+
+    public LogisticRegression(List<Double> weights) {
+        this.weights = weights;
+    }
+
+    @Override
+    public String getName() {
+        return NAME;
+    }
+
+    @Override
+    public XContentBuilder toXContent(XContentBuilder builder, 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;
+        LogisticRegression that = (LogisticRegression) o;
+        return Objects.equals(weights, that.weights);
+    }
+
+    @Override
+    public int hashCode() {
+        return Objects.hash(weights);
+    }
+}

client/rest-high-level/src/test/java/org/elasticsearch/client/RestHighLevelClientTests.java

@@ -68,6 +68,7 @@
 import org.elasticsearch.client.ml.dataframe.evaluation.softclassification.PrecisionMetric;
 import org.elasticsearch.client.ml.dataframe.evaluation.softclassification.RecallMetric;
 import org.elasticsearch.client.ml.inference.trainedmodel.ensemble.Ensemble;
+import org.elasticsearch.client.ml.inference.trainedmodel.ensemble.LogisticRegression;
 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;
@@ -686,7 +687,7 @@ public void testDefaultNamedXContents() {
 
     public void testProvidedNamedXContents() {
         List<NamedXContentRegistry.Entry> namedXContents = RestHighLevelClient.getProvidedNamedXContents();
-        assertEquals(48, namedXContents.size());
+        assertEquals(49, namedXContents.size());
         Map<Class<?>, Integer> categories = new HashMap<>();
         List<String> names = new ArrayList<>();
         for (NamedXContentRegistry.Entry namedXContent : namedXContents) {
@@ -750,9 +751,9 @@ public void testProvidedNamedXContents() {
         assertThat(names, hasItems(FrequencyEncoding.NAME, OneHotEncoding.NAME, TargetMeanEncoding.NAME));
         assertEquals(Integer.valueOf(2), categories.get(org.elasticsearch.client.ml.inference.trainedmodel.TrainedModel.class));
         assertThat(names, hasItems(Tree.NAME, Ensemble.NAME));
-        assertEquals(Integer.valueOf(2),
+        assertEquals(Integer.valueOf(3),
             categories.get(org.elasticsearch.client.ml.inference.trainedmodel.ensemble.OutputAggregator.class));
-        assertThat(names, hasItems(WeightedMode.NAME, WeightedSum.NAME));
+        assertThat(names, hasItems(WeightedMode.NAME, WeightedSum.NAME, LogisticRegression.NAME));
     }
 
     public void testApiNamingConventions() throws Exception {

client/rest-high-level/src/test/java/org/elasticsearch/client/ml/inference/trainedmodel/ensemble/EnsembleTests.java

@@ -68,7 +68,7 @@ public static Ensemble createRandom() {
         OutputAggregator outputAggregator = null;
         if (randomBoolean()) {
             List<Double> weights = Stream.generate(ESTestCase::randomDouble).limit(numberOfModels).collect(Collectors.toList());
-            outputAggregator = randomFrom(new WeightedMode(weights), new WeightedSum(weights));
+            outputAggregator = randomFrom(new WeightedMode(weights), new WeightedSum(weights), new LogisticRegression(weights));
         }
         List<String> categoryLabels = null;
         if (randomBoolean()) {

client/rest-high-level/src/test/java/org/elasticsearch/client/ml/inference/trainedmodel/ensemble/LogisticRegressionTests.java

@@ -0,0 +1,51 @@
+/*
+ * 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.xcontent.XContentParser;
+import org.elasticsearch.test.AbstractXContentTestCase;
+import org.elasticsearch.test.ESTestCase;
+
+import java.io.IOException;
+import java.util.stream.Collectors;
+import java.util.stream.Stream;
+
+
+public class LogisticRegressionTests extends AbstractXContentTestCase<LogisticRegression> {
+
+    LogisticRegression createTestInstance(int numberOfWeights) {
+        return new LogisticRegression(Stream.generate(ESTestCase::randomDouble).limit(numberOfWeights).collect(Collectors.toList()));
+    }
+
+    @Override
+    protected LogisticRegression doParseInstance(XContentParser parser) throws IOException {
+        return LogisticRegression.fromXContent(parser);
+    }
+
+    @Override
+    protected boolean supportsUnknownFields() {
+        return true;
+    }
+
+    @Override
+    protected LogisticRegression createTestInstance() {
+        return randomBoolean() ? new LogisticRegression(null) : createTestInstance(randomIntBetween(1, 100));
+    }
+
+}

x-pack/plugin/core/src/main/java/org/elasticsearch/xpack/core/XPackClientPlugin.java

@@ -148,6 +148,7 @@
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.RegressionConfig;
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.TrainedModel;
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ensemble.Ensemble;
+import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ensemble.LogisticRegression;
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ensemble.OutputAggregator;
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ensemble.WeightedMode;
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ensemble.WeightedSum;
@@ -470,6 +471,9 @@ public List<NamedWriteableRegistry.Entry> getNamedWriteables() {
                 // ML - Inference aggregators
                 new NamedWriteableRegistry.Entry(OutputAggregator.class, WeightedSum.NAME.getPreferredName(), WeightedSum::new),
                 new NamedWriteableRegistry.Entry(OutputAggregator.class, WeightedMode.NAME.getPreferredName(), WeightedMode::new),
+                new NamedWriteableRegistry.Entry(OutputAggregator.class,
+                    LogisticRegression.NAME.getPreferredName(),
+                    LogisticRegression::new),
                 // ML - Inference Results
                 new NamedWriteableRegistry.Entry(InferenceResults.class,
                     ClassificationInferenceResults.NAME,

x-pack/plugin/core/src/main/java/org/elasticsearch/xpack/core/ml/inference/MlInferenceNamedXContentProvider.java

@@ -19,6 +19,7 @@
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.StrictlyParsedTrainedModel;
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ensemble.Ensemble;
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ensemble.LenientlyParsedOutputAggregator;
+import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ensemble.LogisticRegression;
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ensemble.OutputAggregator;
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ensemble.StrictlyParsedOutputAggregator;
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ensemble.WeightedMode;
@@ -67,6 +68,9 @@ public List<NamedXContentRegistry.Entry> getNamedXContentParsers() {
         namedXContent.add(new NamedXContentRegistry.Entry(LenientlyParsedOutputAggregator.class,
             WeightedSum.NAME,
             WeightedSum::fromXContentLenient));
+        namedXContent.add(new NamedXContentRegistry.Entry(LenientlyParsedOutputAggregator.class,
+            LogisticRegression.NAME,
+            LogisticRegression::fromXContentLenient));
 
         // Model Strict
         namedXContent.add(new NamedXContentRegistry.Entry(StrictlyParsedTrainedModel.class, Tree.NAME, Tree::fromXContentStrict));
@@ -79,6 +83,9 @@ public List<NamedXContentRegistry.Entry> getNamedXContentParsers() {
         namedXContent.add(new NamedXContentRegistry.Entry(StrictlyParsedOutputAggregator.class,
             WeightedSum.NAME,
             WeightedSum::fromXContentStrict));
+        namedXContent.add(new NamedXContentRegistry.Entry(StrictlyParsedOutputAggregator.class,
+            LogisticRegression.NAME,
+            LogisticRegression::fromXContentStrict));
 
         return namedXContent;
     }
@@ -105,6 +112,9 @@ public List<NamedWriteableRegistry.Entry> getNamedWriteables() {
         namedWriteables.add(new NamedWriteableRegistry.Entry(OutputAggregator.class,
             WeightedMode.NAME.getPreferredName(),
             WeightedMode::new));
+        namedWriteables.add(new NamedWriteableRegistry.Entry(OutputAggregator.class,
+            LogisticRegression.NAME.getPreferredName(),
+            LogisticRegression::new));
 
         // Inference Results
         namedWriteables.add(new NamedWriteableRegistry.Entry(InferenceResults.class,