Default "prediction_field_name" to (dependent_variable + "_prediction")

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

@@ -126,8 +126,8 @@
 import org.elasticsearch.client.ml.dataframe.PhaseProgress;
 import org.elasticsearch.client.ml.dataframe.QueryConfig;
 import org.elasticsearch.client.ml.dataframe.evaluation.classification.Classification;
-import org.elasticsearch.client.ml.dataframe.evaluation.regression.MeanSquaredErrorMetric;
 import org.elasticsearch.client.ml.dataframe.evaluation.classification.MulticlassConfusionMatrixMetric;
+import org.elasticsearch.client.ml.dataframe.evaluation.regression.MeanSquaredErrorMetric;
 import org.elasticsearch.client.ml.dataframe.evaluation.regression.RSquaredMetric;
 import org.elasticsearch.client.ml.dataframe.evaluation.regression.Regression;
 import org.elasticsearch.client.ml.dataframe.evaluation.softclassification.AucRocMetric;
@@ -1267,6 +1267,7 @@ public void testPutDataFrameAnalyticsConfig_GivenRegression() throws Exception {
                 .setIndex("put-test-dest-index")
                 .build())
             .setAnalysis(org.elasticsearch.client.ml.dataframe.Regression.builder("my_dependent_variable")
+                .setPredictionFieldName("my_dependent_variable_prediction")
                 .setTrainingPercent(80.0)
                 .build())
             .setDescription("this is a regression")
@@ -1301,6 +1302,7 @@ public void testPutDataFrameAnalyticsConfig_GivenClassification() throws Excepti
                 .setIndex("put-test-dest-index")
                 .build())
             .setAnalysis(org.elasticsearch.client.ml.dataframe.Classification.builder("my_dependent_variable")
+                .setPredictionFieldName("my_dependent_variable_prediction")
                 .setTrainingPercent(80.0)
                 .setNumTopClasses(1)
                 .build())

x-pack/plugin/core/src/main/java/org/elasticsearch/xpack/core/ml/dataframe/analyses/Classification.java

@@ -90,7 +90,7 @@ public Classification(String dependentVariable,
         }
         this.dependentVariable = ExceptionsHelper.requireNonNull(dependentVariable, DEPENDENT_VARIABLE);
         this.boostedTreeParams = ExceptionsHelper.requireNonNull(boostedTreeParams, BoostedTreeParams.NAME);
-        this.predictionFieldName = predictionFieldName;
+        this.predictionFieldName = predictionFieldName == null ? dependentVariable + "_prediction" : predictionFieldName;
         this.numTopClasses = numTopClasses == null ? DEFAULT_NUM_TOP_CLASSES : numTopClasses;
         this.trainingPercent = trainingPercent == null ? 100.0 : trainingPercent;
     }
@@ -111,6 +111,10 @@ public String getDependentVariable() {
         return dependentVariable;
     }
 
+    public String getPredictionFieldName() {
+        return predictionFieldName;
+    }
+
     public int getNumTopClasses() {
         return numTopClasses;
     }

x-pack/plugin/core/src/main/java/org/elasticsearch/xpack/core/ml/dataframe/analyses/Regression.java

@@ -70,7 +70,7 @@ public Regression(String dependentVariable,
         }
         this.dependentVariable = ExceptionsHelper.requireNonNull(dependentVariable, DEPENDENT_VARIABLE);
         this.boostedTreeParams = ExceptionsHelper.requireNonNull(boostedTreeParams, BoostedTreeParams.NAME);
-        this.predictionFieldName = predictionFieldName;
+        this.predictionFieldName = predictionFieldName == null ? dependentVariable + "_prediction" : predictionFieldName;
         this.trainingPercent = trainingPercent == null ? 100.0 : trainingPercent;
     }
 
@@ -89,6 +89,10 @@ public String getDependentVariable() {
         return dependentVariable;
     }
 
+    public String getPredictionFieldName() {
+        return predictionFieldName;
+    }
+
     public double getTrainingPercent() {
         return trainingPercent;
     }

x-pack/plugin/core/src/test/java/org/elasticsearch/xpack/core/ml/dataframe/analyses/ClassificationTests.java

@@ -73,6 +73,14 @@ public void testConstructor_GivenNumTopClassesIsGreaterThan1000() {
         assertThat(e.getMessage(), equalTo("[num_top_classes] must be an integer in [0, 1000]"));
     }
 
+    public void testGetPredictionFieldName() {
+        Classification classification = new Classification("foo", BOOSTED_TREE_PARAMS, "result", 3, 50.0);
+        assertThat(classification.getPredictionFieldName(), equalTo("result"));
+
+        classification = new Classification("foo", BOOSTED_TREE_PARAMS, null, 3, 50.0);
+        assertThat(classification.getPredictionFieldName(), equalTo("foo_prediction"));
+    }
+
     public void testGetNumTopClasses() {
         Classification classification = new Classification("foo", BOOSTED_TREE_PARAMS, "result", 7, 1.0);
         assertThat(classification.getNumTopClasses(), equalTo(7));

x-pack/plugin/core/src/test/java/org/elasticsearch/xpack/core/ml/dataframe/analyses/RegressionTests.java

@@ -19,6 +19,8 @@
 
 public class RegressionTests extends AbstractSerializingTestCase<Regression> {
 
+    private static final BoostedTreeParams BOOSTED_TREE_PARAMS = new BoostedTreeParams(0.0, 0.0, 0.5, 500, 1.0);
+
     @Override
     protected Regression doParseInstance(XContentParser parser) throws IOException {
         return Regression.fromXContent(parser, false);
@@ -42,32 +44,45 @@ protected Writeable.Reader<Regression> instanceReader() {
         return Regression::new;
     }
 
-    public void testConstructor_GivenTrainingPercentIsNull() {
-        Regression regression = new Regression("foo", new BoostedTreeParams(0.0, 0.0, 0.5, 500, 1.0), "result", null);
-        assertThat(regression.getTrainingPercent(), equalTo(100.0));
-    }
-
-    public void testConstructor_GivenTrainingPercentIsBoundary() {
-        Regression regression = new Regression("foo", new BoostedTreeParams(0.0, 0.0, 0.5, 500, 1.0), "result", 1.0);
-        assertThat(regression.getTrainingPercent(), equalTo(1.0));
-        regression = new Regression("foo", new BoostedTreeParams(0.0, 0.0, 0.5, 500, 1.0), "result", 100.0);
-        assertThat(regression.getTrainingPercent(), equalTo(100.0));
-    }
-
     public void testConstructor_GivenTrainingPercentIsLessThanOne() {
         ElasticsearchStatusException e = expectThrows(ElasticsearchStatusException.class,
-            () -> new Regression("foo", new BoostedTreeParams(0.0, 0.0, 0.5, 500, 1.0), "result", 0.999));
+            () -> new Regression("foo", BOOSTED_TREE_PARAMS, "result", 0.999));
 
         assertThat(e.getMessage(), equalTo("[training_percent] must be a double in [1, 100]"));
     }
 
     public void testConstructor_GivenTrainingPercentIsGreaterThan100() {
         ElasticsearchStatusException e = expectThrows(ElasticsearchStatusException.class,
-            () -> new Regression("foo", new BoostedTreeParams(0.0, 0.0, 0.5, 500, 1.0), "result", 100.0001));
+            () -> new Regression("foo", BOOSTED_TREE_PARAMS, "result", 100.0001));
 
         assertThat(e.getMessage(), equalTo("[training_percent] must be a double in [1, 100]"));
     }
 
+    public void testGetPredictionFieldName() {
+        Regression regression = new Regression("foo", BOOSTED_TREE_PARAMS, "result", 50.0);
+        assertThat(regression.getPredictionFieldName(), equalTo("result"));
+
+        regression = new Regression("foo", BOOSTED_TREE_PARAMS, null, 50.0);
+        assertThat(regression.getPredictionFieldName(), equalTo("foo_prediction"));
+    }
+
+    public void testGetTrainingPercent() {
+        Regression regression = new Regression("foo", BOOSTED_TREE_PARAMS, "result", 50.0);
+        assertThat(regression.getTrainingPercent(), equalTo(50.0));
+
+        // Boundary condition: training_percent == 1.0
+        regression = new Regression("foo", BOOSTED_TREE_PARAMS, "result", 1.0);
+        assertThat(regression.getTrainingPercent(), equalTo(1.0));
+
+        // Boundary condition: training_percent == 100.0
+        regression = new Regression("foo", BOOSTED_TREE_PARAMS, "result", 100.0);
+        assertThat(regression.getTrainingPercent(), equalTo(100.0));
+
+        // training_percent == null, default applied
+        regression = new Regression("foo", BOOSTED_TREE_PARAMS, "result", null);
+        assertThat(regression.getTrainingPercent(), equalTo(100.0));
+    }
+
     public void testFieldCardinalityLimitsIsNonNull() {
         assertThat(createTestInstance().getFieldCardinalityLimits(), is(not(nullValue())));
     }

x-pack/plugin/src/test/resources/rest-api-spec/test/ml/data_frame_analytics_crud.yml

@@ -1470,6 +1470,7 @@ setup:
       "eta": 0.5,
       "maximum_number_trees": 400,
       "feature_bag_fraction": 0.3,
+      "prediction_field_name": "foo_prediction",
       "training_percent": 60.3
     }
   }}
@@ -1809,6 +1810,7 @@ setup:
       "eta": 0.5,
       "maximum_number_trees": 400,
       "feature_bag_fraction": 0.3,
+      "prediction_field_name": "foo_prediction",
       "training_percent": 60.3,
       "num_top_classes": 2
     }
@@ -1844,6 +1846,7 @@ setup:
   - match: { analysis: {
     "regression":{
       "dependent_variable": "foo",
+      "prediction_field_name": "foo_prediction",
       "training_percent": 100.0
     }
   }}

x-pack/qa/rolling-upgrade/src/test/resources/rest-api-spec/test/mixed_cluster/90_ml_data_frame_analytics_crud.yml

@@ -58,7 +58,8 @@
   - match: { data_frame_analytics.0.source.index: ["bwc_ml_regression_job_source"] }
   - match: { data_frame_analytics.0.source.query: {"term": { "user": "Kimchy" }} }
   - match: { data_frame_analytics.0.dest.index: "old_cluster_regression_job_results" }
-  - match: { data_frame_analytics.0.analysis: {"regression":{ "dependent_variable": "foo", "training_percent": 100.0 }} }
+  - match: { data_frame_analytics.0.analysis.regression.dependent_variable: "foo" }
+  - match: { data_frame_analytics.0.analysis.regression.training_percent: 100.0 }
 
 ---
 "Get old regression job stats":

x-pack/qa/rolling-upgrade/src/test/resources/rest-api-spec/test/upgraded_cluster/90_ml_data_frame_analytics_crud.yml

@@ -38,7 +38,8 @@
   - match: { data_frame_analytics.0.source.index: ["bwc_ml_regression_job_source"] }
   - match: { data_frame_analytics.0.source.query: {"term": { "user": "Kimchy" }} }
   - match: { data_frame_analytics.0.dest.index: "old_cluster_regression_job_results" }
-  - match: { data_frame_analytics.0.analysis: {"regression":{ "dependent_variable": "foo", "training_percent": 100.0 }} }
+  - match: { data_frame_analytics.0.analysis.regression.dependent_variable: "foo" }
+  - match: { data_frame_analytics.0.analysis.regression.training_percent: 100.0 }
 
 ---
 "Get old cluster regression job stats":