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Move ML-Plan model selection to new Maven module
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+61
-52
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6 files changed

+61
-52
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‎ml2plan-model-selection/pom.xml‎

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<?xml version="1.0" encoding="UTF-8"?>
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<project xmlns="http://maven.apache.org/POM/4.0.0"
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xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
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xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
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<modelVersion>4.0.0</modelVersion>
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<parent>
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<groupId>de.fraunhofer.iem</groupId>
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<artifactId>swan</artifactId>
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<version>3.3.1</version>
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</parent>
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<artifactId>ml2plan-model-selection</artifactId>
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<properties>
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<maven.compiler.source>17</maven.compiler.source>
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<maven.compiler.target>17</maven.compiler.target>
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<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
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</properties>
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<repositories>
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<repository>
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<id>scijava-public</id>
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<url>https://maven.scijava.org/content/repositories/public/</url>
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</repository>
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</repositories>
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<dependencies>
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<dependency>
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<groupId>ai.libs</groupId>
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<artifactId>hasco-core</artifactId>
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<version>0.2.7</version>
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</dependency>
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<dependency>
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<groupId>ai.libs</groupId>
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<artifactId>jaicore-algorithminspector</artifactId>
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<version>0.2.7</version>
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</dependency>
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<dependency>
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<groupId>ai.libs</groupId>
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<artifactId>mlplan-meka</artifactId>
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<version>0.2.7</version>
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</dependency>
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<dependency>
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<groupId>org.graphstream</groupId>
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<artifactId>gs-ui-javafx</artifactId>
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<version>2.0</version>
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</dependency>
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<dependency>
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<groupId>com.github.mwever</groupId>
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<artifactId>gs-core</artifactId>
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<version>2.0.2-synchrofix</version>
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</dependency>
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</dependencies>
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</project>

swan-cmd/src/main/java/de/fraunhofer/iem/swan/model/toolkit/ML2Plan.java renamed to ml2plan-model-selection/src/main/java/de/fraunhofer/iem/ML2Plan.java

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package de.fraunhofer.iem.swan.model.toolkit;
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package de.fraunhofer.iem;
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import ai.libs.jaicore.ml.classification.multilabel.dataset.IMekaInstances;
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import ai.libs.jaicore.ml.classification.multilabel.dataset.MekaInstances;
@@ -8,10 +8,6 @@
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import ai.libs.jaicore.ml.core.filter.SplitterUtil;
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import ai.libs.mlplan.core.MLPlan;
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import ai.libs.mlplan.meka.ML2PlanMekaBuilder;
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import de.fraunhofer.iem.swan.cli.SwanOptions;
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import de.fraunhofer.iem.swan.features.MekaFeatureSet;
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import de.fraunhofer.iem.swan.io.dataset.SrmList;
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import de.fraunhofer.iem.swan.model.ModelEvaluator;
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import meka.core.MLUtils;
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import org.api4.java.ai.ml.classification.multilabel.evaluation.IMultiLabelClassification;
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import org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset;
@@ -32,34 +28,14 @@
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public class ML2Plan {
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private static final Logger LOGGER = LoggerFactory.getLogger(ML2Plan.class);
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private MekaFeatureSet featureSet;
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/* private MekaFeatureSet featureSet;
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private SwanOptions swanOptions;
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public ML2Plan(MekaFeatureSet features, SwanOptions options) {
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this.featureSet = features;
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swanOptions = options;
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}
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/**
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* Trains and evaluates the model with the given training data and specified classification mode.
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*
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* @return Hashmap containing the name of the classifier and it's F-Measure
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*/
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public SrmList trainModel() {
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switch (ModelEvaluator.Phase.valueOf(swanOptions.getPhase().toUpperCase())) {
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case VALIDATE:
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}*/
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try {
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crossValidate(featureSet.getTrainInstances().get("meka"));
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} catch (Exception e) {
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throw new RuntimeException(e);
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}
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return null;
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case PREDICT:
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}
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return null;
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}
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public void crossValidate(Instances instances) throws Exception {
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‎swan-cmd/pom.xml‎

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<artifactId>deeplearning4j-nlp</artifactId>
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<version>${dl4j-master.version}</version>
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</dependency>
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<dependency>
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<groupId>ai.libs</groupId>
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<artifactId>mlplan-meka</artifactId>
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<version>0.2.7</version>
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</dependency>
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<dependency>
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<groupId>org.graphstream</groupId>
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<artifactId>gs-ui-javafx</artifactId>
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<version>2.0</version>
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</dependency>
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<dependency>
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<groupId>ai.libs</groupId>
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<artifactId>hasco-core</artifactId>
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<version>0.2.7</version>
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</dependency>
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<dependency>
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<groupId>org.slf4j</groupId>
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<artifactId>slf4j-api</artifactId>

‎swan-cmd/src/main/java/de/fraunhofer/iem/swan/cli/CliRunner.java‎

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@@ -35,7 +35,7 @@ public class CliRunner implements Callable<Integer> {
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@CommandLine.Option(names = {"-f", "--feature"}, arity = "1..*", description = {"Select one or more feature sets: all, code, code-br, doc-auto or doc-manual"})
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private List<String> featureSet = Collections.singletonList("code");
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@CommandLine.Option(names = {"-t", "--toolkit"}, description = {"ML toolkit: meka, weka, ml2plan"})
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@CommandLine.Option(names = {"-t", "--toolkit"}, description = {"ML toolkit: meka, weka"})
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private String toolkit = "meka";
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@CommandLine.Option(names = {"-s", "--srm"}, description = {"SRM: all, source, sink, sanitizer, authentication"})

‎swan-cmd/src/main/java/de/fraunhofer/iem/swan/features/FeatureSetSelector.java‎

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@@ -10,7 +10,6 @@ public IFeatureSet select(Dataset dataset, SwanOptions options) {
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switch (ModelEvaluator.Toolkit.valueOf(options.getToolkit().toUpperCase())) {
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case ML2PLAN:
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case MEKA:
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MekaFeatureSet mekaFeatureSet = new MekaFeatureSet(dataset, options);
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mekaFeatureSet.createFeatures();

‎swan-cmd/src/main/java/de/fraunhofer/iem/swan/model/ModelEvaluator.java‎

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@@ -9,7 +9,6 @@
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import de.fraunhofer.iem.swan.io.dataset.Dataset;
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import de.fraunhofer.iem.swan.io.dataset.SrmList;
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import de.fraunhofer.iem.swan.io.dataset.SrmListUtils;
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import de.fraunhofer.iem.swan.model.toolkit.ML2Plan;
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import de.fraunhofer.iem.swan.model.toolkit.Meka;
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import de.fraunhofer.iem.swan.model.toolkit.Weka;
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import org.slf4j.Logger;
@@ -30,8 +29,7 @@ public class ModelEvaluator {
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public enum Toolkit {
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WEKA,
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MEKA,
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ML2PLAN
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MEKA
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}
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public enum Phase {
@@ -70,11 +68,6 @@ public void trainModel() {
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Weka weka = new Weka((WekaFeatureSet) features, options, dataset.getTestMethods());
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processResults(weka.trainModel());
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break;
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case ML2PLAN:
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logger.info("Evaluating model with ML-PLAN");
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ML2Plan mlPlan = new ML2Plan((MekaFeatureSet) features, options);
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processResults(mlPlan.trainModel());
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break;
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}
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}
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