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[7.x] Implement evaluation API for multiclass classification problem (#…
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przemekwitek authored Oct 4, 2019
1 parent e3aab12 commit ee952da
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Showing 20 changed files with 1,963 additions and 41 deletions.
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Expand Up @@ -18,7 +18,9 @@
*/
package org.elasticsearch.client.ml.dataframe.evaluation;

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.RSquaredMetric;
import org.elasticsearch.client.ml.dataframe.evaluation.regression.Regression;
import org.elasticsearch.client.ml.dataframe.evaluation.softclassification.BinarySoftClassification;
Expand All @@ -41,13 +43,18 @@ public List<NamedXContentRegistry.Entry> getNamedXContentParsers() {
// Evaluations
new NamedXContentRegistry.Entry(
Evaluation.class, new ParseField(BinarySoftClassification.NAME), BinarySoftClassification::fromXContent),
new NamedXContentRegistry.Entry(Evaluation.class, new ParseField(Classification.NAME), Classification::fromXContent),
new NamedXContentRegistry.Entry(Evaluation.class, new ParseField(Regression.NAME), Regression::fromXContent),
// Evaluation metrics
new NamedXContentRegistry.Entry(EvaluationMetric.class, new ParseField(AucRocMetric.NAME), AucRocMetric::fromXContent),
new NamedXContentRegistry.Entry(EvaluationMetric.class, new ParseField(PrecisionMetric.NAME), PrecisionMetric::fromXContent),
new NamedXContentRegistry.Entry(EvaluationMetric.class, new ParseField(RecallMetric.NAME), RecallMetric::fromXContent),
new NamedXContentRegistry.Entry(
EvaluationMetric.class, new ParseField(ConfusionMatrixMetric.NAME), ConfusionMatrixMetric::fromXContent),
new NamedXContentRegistry.Entry(
EvaluationMetric.class,
new ParseField(MulticlassConfusionMatrixMetric.NAME),
MulticlassConfusionMatrixMetric::fromXContent),
new NamedXContentRegistry.Entry(
EvaluationMetric.class, new ParseField(MeanSquaredErrorMetric.NAME), MeanSquaredErrorMetric::fromXContent),
new NamedXContentRegistry.Entry(
Expand All @@ -60,10 +67,14 @@ EvaluationMetric.Result.class, new ParseField(PrecisionMetric.NAME), PrecisionMe
new NamedXContentRegistry.Entry(
EvaluationMetric.Result.class, new ParseField(RecallMetric.NAME), RecallMetric.Result::fromXContent),
new NamedXContentRegistry.Entry(
EvaluationMetric.Result.class, new ParseField(RSquaredMetric.NAME), RSquaredMetric.Result::fromXContent),
EvaluationMetric.Result.class, new ParseField(ConfusionMatrixMetric.NAME), ConfusionMatrixMetric.Result::fromXContent),
new NamedXContentRegistry.Entry(
EvaluationMetric.Result.class,
new ParseField(MulticlassConfusionMatrixMetric.NAME),
MulticlassConfusionMatrixMetric.Result::fromXContent),
new NamedXContentRegistry.Entry(
EvaluationMetric.Result.class, new ParseField(MeanSquaredErrorMetric.NAME), MeanSquaredErrorMetric.Result::fromXContent),
new NamedXContentRegistry.Entry(
EvaluationMetric.Result.class, new ParseField(ConfusionMatrixMetric.NAME), ConfusionMatrixMetric.Result::fromXContent));
EvaluationMetric.Result.class, new ParseField(RSquaredMetric.NAME), RSquaredMetric.Result::fromXContent));
}
}
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@@ -0,0 +1,132 @@
/*
* 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.dataframe.evaluation.classification;

import org.elasticsearch.client.ml.dataframe.evaluation.Evaluation;
import org.elasticsearch.client.ml.dataframe.evaluation.EvaluationMetric;
import org.elasticsearch.common.Nullable;
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.Arrays;
import java.util.Comparator;
import java.util.List;
import java.util.Objects;

/**
* Evaluation of classification results.
*/
public class Classification implements Evaluation {

public static final String NAME = "classification";

private static final ParseField ACTUAL_FIELD = new ParseField("actual_field");
private static final ParseField PREDICTED_FIELD = new ParseField("predicted_field");
private static final ParseField METRICS = new ParseField("metrics");

@SuppressWarnings("unchecked")
public static final ConstructingObjectParser<Classification, Void> PARSER = new ConstructingObjectParser<>(
NAME, true, a -> new Classification((String) a[0], (String) a[1], (List<EvaluationMetric>) a[2]));

static {
PARSER.declareString(ConstructingObjectParser.constructorArg(), ACTUAL_FIELD);
PARSER.declareString(ConstructingObjectParser.constructorArg(), PREDICTED_FIELD);
PARSER.declareNamedObjects(ConstructingObjectParser.optionalConstructorArg(),
(p, c, n) -> p.namedObject(EvaluationMetric.class, n, c), METRICS);
}

public static Classification fromXContent(XContentParser parser) {
return PARSER.apply(parser, null);
}

/**
* The field containing the actual value
* The value of this field is assumed to be numeric
*/
private final String actualField;

/**
* The field containing the predicted value
* The value of this field is assumed to be numeric
*/
private final String predictedField;

/**
* The list of metrics to calculate
*/
private final List<EvaluationMetric> metrics;

public Classification(String actualField, String predictedField) {
this(actualField, predictedField, (List<EvaluationMetric>)null);
}

public Classification(String actualField, String predictedField, EvaluationMetric... metrics) {
this(actualField, predictedField, Arrays.asList(metrics));
}

public Classification(String actualField, String predictedField, @Nullable List<EvaluationMetric> metrics) {
this.actualField = Objects.requireNonNull(actualField);
this.predictedField = Objects.requireNonNull(predictedField);
if (metrics != null) {
metrics.sort(Comparator.comparing(EvaluationMetric::getName));
}
this.metrics = metrics;
}

@Override
public String getName() {
return NAME;
}

@Override
public XContentBuilder toXContent(XContentBuilder builder, Params params) throws IOException {
builder.startObject();
builder.field(ACTUAL_FIELD.getPreferredName(), actualField);
builder.field(PREDICTED_FIELD.getPreferredName(), predictedField);

if (metrics != null) {
builder.startObject(METRICS.getPreferredName());
for (EvaluationMetric metric : metrics) {
builder.field(metric.getName(), metric);
}
builder.endObject();
}

builder.endObject();
return builder;
}

@Override
public boolean equals(Object o) {
if (this == o) return true;
if (o == null || getClass() != o.getClass()) return false;
Classification that = (Classification) o;
return Objects.equals(that.actualField, this.actualField)
&& Objects.equals(that.predictedField, this.predictedField)
&& Objects.equals(that.metrics, this.metrics);
}

@Override
public int hashCode() {
return Objects.hash(actualField, predictedField, metrics);
}
}
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@@ -0,0 +1,164 @@
/*
* 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.dataframe.evaluation.classification;

import org.elasticsearch.client.ml.dataframe.evaluation.EvaluationMetric;
import org.elasticsearch.common.Nullable;
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.Collections;
import java.util.Map;
import java.util.Objects;
import java.util.TreeMap;

import static org.elasticsearch.common.xcontent.ConstructingObjectParser.constructorArg;
import static org.elasticsearch.common.xcontent.ConstructingObjectParser.optionalConstructorArg;

/**
* Calculates the multiclass confusion matrix.
*/
public class MulticlassConfusionMatrixMetric implements EvaluationMetric {

public static final String NAME = "multiclass_confusion_matrix";

public static final ParseField SIZE = new ParseField("size");

private static final ConstructingObjectParser<MulticlassConfusionMatrixMetric, Void> PARSER = createParser();

private static ConstructingObjectParser<MulticlassConfusionMatrixMetric, Void> createParser() {
ConstructingObjectParser<MulticlassConfusionMatrixMetric, Void> parser =
new ConstructingObjectParser<>(NAME, true, args -> new MulticlassConfusionMatrixMetric((Integer) args[0]));
parser.declareInt(optionalConstructorArg(), SIZE);
return parser;
}

public static MulticlassConfusionMatrixMetric fromXContent(XContentParser parser) {
return PARSER.apply(parser, null);
}

private final Integer size;

public MulticlassConfusionMatrixMetric() {
this(null);
}

public MulticlassConfusionMatrixMetric(@Nullable Integer size) {
this.size = size;
}

@Override
public String getName() {
return NAME;
}

@Override
public XContentBuilder toXContent(XContentBuilder builder, Params params) throws IOException {
builder.startObject();
if (size != null) {
builder.field(SIZE.getPreferredName(), size);
}
builder.endObject();
return builder;
}

@Override
public boolean equals(Object o) {
if (this == o) return true;
if (o == null || getClass() != o.getClass()) return false;
MulticlassConfusionMatrixMetric that = (MulticlassConfusionMatrixMetric) o;
return Objects.equals(this.size, that.size);
}

@Override
public int hashCode() {
return Objects.hash(size);
}

public static class Result implements EvaluationMetric.Result {

private static final ParseField CONFUSION_MATRIX = new ParseField("confusion_matrix");
private static final ParseField OTHER_CLASSES_COUNT = new ParseField("_other_");

@SuppressWarnings("unchecked")
private static final ConstructingObjectParser<Result, Void> PARSER =
new ConstructingObjectParser<>(
"multiclass_confusion_matrix_result", true, a -> new Result((Map<String, Map<String, Long>>) a[0], (long) a[1]));

static {
PARSER.declareObject(
constructorArg(),
(p, c) -> p.map(TreeMap::new, p2 -> p2.map(TreeMap::new, XContentParser::longValue)),
CONFUSION_MATRIX);
PARSER.declareLong(constructorArg(), OTHER_CLASSES_COUNT);
}

public static Result fromXContent(XContentParser parser) {
return PARSER.apply(parser, null);
}

// Immutable
private final Map<String, Map<String, Long>> confusionMatrix;
private final long otherClassesCount;

public Result(Map<String, Map<String, Long>> confusionMatrix, long otherClassesCount) {
this.confusionMatrix = Collections.unmodifiableMap(Objects.requireNonNull(confusionMatrix));
this.otherClassesCount = otherClassesCount;
}

@Override
public String getMetricName() {
return NAME;
}

public Map<String, Map<String, Long>> getConfusionMatrix() {
return confusionMatrix;
}

public long getOtherClassesCount() {
return otherClassesCount;
}

@Override
public XContentBuilder toXContent(XContentBuilder builder, Params params) throws IOException {
builder.startObject();
builder.field(CONFUSION_MATRIX.getPreferredName(), confusionMatrix);
builder.field(OTHER_CLASSES_COUNT.getPreferredName(), otherClassesCount);
builder.endObject();
return builder;
}

@Override
public boolean equals(Object o) {
if (this == o) return true;
if (o == null || getClass() != o.getClass()) return false;
Result that = (Result) o;
return Objects.equals(this.confusionMatrix, that.confusionMatrix)
&& this.otherClassesCount == that.otherClassesCount;
}

@Override
public int hashCode() {
return Objects.hash(confusionMatrix, otherClassesCount);
}
}
}
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