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[ML] Make Ensemble feature names optional (#51996) 

The featureNames field is requisite in individual models but is not required by the Ensemble.
This commit is contained in:
David Kyle 2020-02-07 10:07:18 +00:00
parent 91e938ead8
commit 8f10a7c6ca
5 changed files with 11 additions and 8 deletions
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4
client/rest-high-level/src/main/java/org/elasticsearch/client/ml/inference/trainedmodel/ensemble/Ensemble.java
View File

@ -103,7 +103,7 @@ public class Ensemble implements TrainedModel {
@Override
public XContentBuilder toXContent(XContentBuilder builder, ToXContent.Params params) throws IOException {
builder.startObject();
if (featureNames != null) {
if (featureNames != null && featureNames.isEmpty() == false) {
builder.field(FEATURE_NAMES.getPreferredName(), featureNames);
}
if (models != null) {
@ -157,7 +157,7 @@ public class Ensemble implements TrainedModel {
}
public static class Builder {
private List<String> featureNames;
private List<String> featureNames = Collections.emptyList();
private List<TrainedModel> trainedModels;
private OutputAggregator outputAggregator;
private TargetType targetType;

2
client/rest-high-level/src/test/java/org/elasticsearch/client/ml/inference/trainedmodel/ensemble/EnsembleTests.java
View File

@ -86,7 +86,7 @@ public class EnsembleTests extends AbstractXContentTestCase<Ensemble> {
.toArray() :
null;
return new Ensemble(featureNames,
return new Ensemble(randomBoolean() ? featureNames : Collections.emptyList(),
models,
outputAggregator,
targetType,

4
docs/reference/ml/df-analytics/apis/put-inference.asciidoc
View File

@ -150,7 +150,7 @@ See <<ml-put-inference-preprocessor-example>> for more details.
The definition for a binary decision tree.
`tree`.`feature_names`:::
(Required, string)
(Required, string)
Features expected by the tree, in their expected order.
`tree`.`tree_structure`:::
@ -221,7 +221,7 @@ children).
The definition for an ensemble model.
`ensemble`.`feature_names`:::
(Required, string)
(Optional, string)
Features expected by the ensemble, in their expected order.
`ensemble`.`trained_models`:::

7
x-pack/plugin/core/src/main/java/org/elasticsearch/xpack/core/ml/inference/trainedmodel/ensemble/Ensemble.java
View File

@ -207,7 +207,9 @@ public class Ensemble implements LenientlyParsedTrainedModel, StrictlyParsedTrai
@Override
public XContentBuilder toXContent(XContentBuilder builder, Params params) throws IOException {
builder.startObject();
builder.field(FEATURE_NAMES.getPreferredName(), featureNames);
if (featureNames.isEmpty() == false) {
builder.field(FEATURE_NAMES.getPreferredName(), featureNames);
}
NamedXContentObjectHelper.writeNamedObjects(builder, params, true, TRAINED_MODELS.getPreferredName(), models);
NamedXContentObjectHelper.writeNamedObjects(builder,
params,
@ -327,8 +329,9 @@ public class Ensemble implements LenientlyParsedTrainedModel, StrictlyParsedTrai
private double[] classificationWeights;
private boolean modelsAreOrdered;
private Builder (boolean modelsAreOrdered) {
private Builder(boolean modelsAreOrdered) {
this.modelsAreOrdered = modelsAreOrdered;
this.featureNames = Collections.emptyList();
}
private static Builder builderForParser() {

2
x-pack/plugin/core/src/test/java/org/elasticsearch/xpack/core/ml/inference/trainedmodel/ensemble/EnsembleTests.java
View File

@ -92,7 +92,7 @@ public class EnsembleTests extends AbstractSerializingTestCase<Ensemble> {
.toArray() :
null;
return new Ensemble(featureNames,
return new Ensemble(randomBoolean() ? featureNames : Collections.emptyList(),
models,
outputAggregator,
targetType,