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New algorithms and functionalities
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News algorithms
Improvements in configuration files
Documentation and API update
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azafra committed Apr 4, 2024
1 parent 26c6f73 commit f0e7525
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35 changes: 35 additions & 0 deletions dist/configurations/toMI/MIMLtoMI_BR_MINND.config
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<configuration>

<classifier name="miml.classifiers.miml.mimlTOmi.MIMLClassifierToMI">

<transformationMethod name="miml.classifiers.miml.mimlTOmi.MIMLBinaryRelevance"/>

<multiInstanceClassifier name="weka.classifiers.mi.MINND">
<listOptions>
-K 10 -S 1 -E 1
</listOptions>
</multiInstanceClassifier>

</classifier>

<evaluator name="miml.evaluation.EvaluatorHoldout">
<data>
<trainFile>data/miml_birds_random_80train.arff</trainFile>
<testFile>data/miml_birds_random_20test.arff</testFile>
<xmlFile>data/miml_birds.xml</xmlFile>
</data>
</evaluator>

<report name="miml.report.BaseMIMLReport">
<fileName>results/toMI/BR_MINND.csv</fileName>
<standardDeviation>false</standardDeviation>
<header>true</header>
<measures perLabel="false">
<measure>Hamming Loss</measure>
<measure>Subset Accuracy</measure>
<measure>Macro-averaged Precision</measure>
<measure>Macro-averaged F-Measure</measure>
</measures>
</report>

</configuration>
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35 changes: 35 additions & 0 deletions dist/configurations/toMI/MIMLtoMI_BR_TLC.config
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<configuration>

<classifier name="miml.classifiers.miml.mimlTOmi.MIMLClassifierToMI">

<transformationMethod name="miml.classifiers.miml.mimlTOmi.MIMLBinaryRelevance"/>

<multiInstanceClassifier name="weka.classifiers.mi.TLC">
<listOptions>
-P weka.classifiers.trees.J48 -W weka.classifiers.meta.LogitBoost -- -S 1 -I 10 -W weka.classifiers.trees.DecisionStump
</listOptions>
</multiInstanceClassifier>

</classifier>

<evaluator name="miml.evaluation.EvaluatorHoldout">
<data>
<trainFile>data/miml_birds_random_80train.arff</trainFile>
<testFile>data/miml_birds_random_20test.arff</testFile>
<xmlFile>data/miml_birds.xml</xmlFile>
</data>
</evaluator>

<report name="miml.report.BaseMIMLReport">
<fileName>results/toMI/BR_TLC.csv</fileName>
<standardDeviation>false</standardDeviation>
<header>true</header>
<measures perLabel="false">
<measure>Hamming Loss</measure>
<measure>Subset Accuracy</measure>
<measure>Macro-averaged Precision</measure>
<measure>Macro-averaged F-Measure</measure>
</measures>
</report>

</configuration>
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35 changes: 35 additions & 0 deletions dist/configurations/toMI/MIMLtoMI_LP_MINND.config
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<configuration>

<classifier name="miml.classifiers.miml.mimlTOmi.MIMLClassifierToMI">

<transformationMethod name="miml.classifiers.miml.mimlTOmi.MIMLLabelPowerset"/>

<multiInstanceClassifier name="weka.classifiers.mi.MINND">
<listOptions>
-K 10 -S 1 -E 1
</listOptions>
</multiInstanceClassifier>

</classifier>

<evaluator name="miml.evaluation.EvaluatorHoldout">
<data>
<trainFile>data/miml_birds_random_80train.arff</trainFile>
<testFile>data/miml_birds_random_20test.arff</testFile>
<xmlFile>data/miml_birds.xml</xmlFile>
</data>
</evaluator>

<report name="miml.report.BaseMIMLReport">
<fileName>results/toMI/LP_MINND.csv</fileName>
<standardDeviation>false</standardDeviation>
<header>true</header>
<measures perLabel="false">
<measure>Hamming Loss</measure>
<measure>Subset Accuracy</measure>
<measure>Macro-averaged Precision</measure>
<measure>Macro-averaged F-Measure</measure>
</measures>
</report>

</configuration>
35 changes: 35 additions & 0 deletions dist/configurations/toMI/MIMLtoMI_LP_MISMO.config
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<configuration>

<classifier name="miml.classifiers.miml.mimlTOmi.MIMLClassifierToMI">

<transformationMethod name="miml.classifiers.miml.mimlTOmi.MIMLLabelPowerset"/>

<multiInstanceClassifier name="miml.classifiers.mi.MISMOWrapper">
<listOptions>
-L 1.0e-3 -P 1.0e-12 -N 0 -V 5
</listOptions>
</multiInstanceClassifier>

</classifier>

<evaluator name="miml.evaluation.EvaluatorHoldout">
<data>
<trainFile>data/miml_birds_random_80train.arff</trainFile>
<testFile>data/miml_birds_random_20test.arff</testFile>
<xmlFile>data/miml_birds.xml</xmlFile>
</data>
</evaluator>

<report name="miml.report.BaseMIMLReport">
<fileName>results/toMI/LP_MISMO.csv</fileName>
<standardDeviation>false</standardDeviation>
<header>true</header>
<measures perLabel="false">
<measure>Hamming Loss</measure>
<measure>Subset Accuracy</measure>
<measure>Macro-averaged Precision</measure>
<measure>Macro-averaged F-Measure</measure>
</measures>
</report>

</configuration>
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35 changes: 35 additions & 0 deletions dist/configurations/toMI/MIMLtoMI_LP_TLC.config
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<configuration>

<classifier name="miml.classifiers.miml.mimlTOmi.MIMLClassifierToMI">

<transformationMethod name="miml.classifiers.miml.mimlTOmi.MIMLLabelPowerset"/>

<multiInstanceClassifier name="weka.classifiers.mi.TLC">
<listOptions>
-P weka.classifiers.trees.J48 -W weka.classifiers.meta.LogitBoost -- -S 1 -I 10 -W weka.classifiers.trees.DecisionStump
</listOptions>
</multiInstanceClassifier>

</classifier>

<evaluator name="miml.evaluation.EvaluatorHoldout">
<data>
<trainFile>data/miml_birds_random_80train.arff</trainFile>
<testFile>data/miml_birds_random_20test.arff</testFile>
<xmlFile>data/miml_birds.xml</xmlFile>
</data>
</evaluator>

<report name="miml.report.BaseMIMLReport">
<fileName>results/toMI/LP_TLC.csv</fileName>
<standardDeviation>false</standardDeviation>
<header>true</header>
<measures perLabel="false">
<measure>Hamming Loss</measure>
<measure>Subset Accuracy</measure>
<measure>Macro-averaged Precision</measure>
<measure>Macro-averaged F-Measure</measure>
</measures>
</report>

</configuration>
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33 changes: 33 additions & 0 deletions dist/configurations/toML/MIMLtoML_AT_MLDGC.config
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<configuration>

<classifier name="miml.classifiers.miml.mimlTOml.MIMLClassifierToML">

<multiLabelClassifier name="miml.classifiers.ml.MLDGC">
<parameters>
<parameter class="int.class" value="10"/>
</parameters>
</multiLabelClassifier>
<transformationMethod name="miml.transformation.mimlTOml.ArithmeticTransformation"/>
</classifier>

<evaluator name="miml.evaluation.EvaluatorCV">
<numFolds>5</numFolds>
<data>
<file>data/miml_birds.arff</file>
<xmlFile>data/miml_birds.xml</xmlFile>
</data>
</evaluator>

<report name="miml.report.BaseMIMLReport">
<fileName>results/toML/AT_MLDGC.csv</fileName>
<standardDeviation>false</standardDeviation>
<header>true</header>
<measures perLabel="false">
<measure>Hamming Loss</measure>
<measure>Subset Accuracy</measure>
<measure>Macro-averaged Precision</measure>
<measure>Macro-averaged F-Measure</measure>
</measures>
</report>

</configuration>
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<configuration>

<classifier name="miml.classifiers.miml.mimlTOml.MIMLClassifierToML">

<multiLabelClassifier name="miml.classifiers.ml.RFPCT">
<parameters>
<parameter class="String.class" value="clusFolder"/>
<parameter class="String.class" value="clusBirds"/>
<parameter class="int.class" value="10"/>
<parameter class="long.class" value="1"/>
</parameters>
</multiLabelClassifier>
<transformationMethod name="miml.transformation.mimlTOml.ArithmeticTransformation"/>
</classifier>

<evaluator name="miml.evaluation.EvaluatorHoldoutClus">
<data>
<trainFile>data/miml_birds_random_80train.arff</trainFile>
<testFile>data/miml_birds_random_20test.arff</testFile>
<xmlFile>data/miml_birds.xml</xmlFile>
</data>
<clusWorkingDir>clusFolder</clusWorkingDir>
<clusDataset>clusBirds</clusDataset>
</evaluator>


<report name="miml.report.BaseMIMLReport">
<fileName>results/toML/AT_RFPCT.csv</fileName>
<standardDeviation>false</standardDeviation>
<header>true</header>
<measures perLabel="false">
<measure>Hamming Loss</measure>
<measure>Subset Accuracy</measure>
<measure>Macro-averaged Precision</measure>
<measure>Macro-averaged F-Measure</measure>
</measures>
</report>

</configuration>
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29 changes: 29 additions & 0 deletions dist/configurations/toML/MIMLtoML_GT_MLDGC.config
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<configuration>

<classifier name="miml.classifiers.miml.mimlTOml.MIMLClassifierToML">

<multiLabelClassifier name="miml.classifiers.ml.MLDGC"/>
<transformationMethod name="miml.transformation.mimlTOml.GeometricTransformation"/>
</classifier>

<evaluator name="miml.evaluation.EvaluatorCV">
<numFolds>5</numFolds>
<data>
<file>data/miml_birds.arff</file>
<xmlFile>data/miml_birds.xml</xmlFile>
</data>
</evaluator>

<report name="miml.report.BaseMIMLReport">
<fileName>results/toML/GT_MLDGC.csv</fileName>
<standardDeviation>false</standardDeviation>
<header>true</header>
<measures perLabel="false">
<measure>Hamming Loss</measure>
<measure>Subset Accuracy</measure>
<measure>Macro-averaged Precision</measure>
<measure>Macro-averaged F-Measure</measure>
</measures>
</report>

</configuration>
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39 changes: 39 additions & 0 deletions dist/configurations/toML/MIMLtoML_GT_RFPCT.config
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<configuration>

<classifier name="miml.classifiers.miml.mimlTOml.MIMLClassifierToML">

<multiLabelClassifier name="miml.classifiers.ml.RFPCT">
<parameters>
<parameter class="String.class" value="clusFolder"/>
<parameter class="String.class" value="clusBirds"/>
<parameter class="int.class" value="10"/>
<parameter class="long.class" value="1"/>
</parameters>
</multiLabelClassifier>
<transformationMethod name="miml.transformation.mimlTOml.GeometricTransformation"/>
</classifier>

<evaluator name="miml.evaluation.EvaluatorHoldoutClus">
<data>
<trainFile>data/miml_birds_random_80train.arff</trainFile>
<testFile>data/miml_birds_random_20test.arff</testFile>
<xmlFile>data/miml_birds.xml</xmlFile>
</data>
<clusWorkingDir>clusFolder</clusWorkingDir>
<clusDataset>clusBirds</clusDataset>
</evaluator>


<report name="miml.report.BaseMIMLReport">
<fileName>results/toML/GT_RFPCT.csv</fileName>
<standardDeviation>false</standardDeviation>
<header>true</header>
<measures perLabel="false">
<measure>Hamming Loss</measure>
<measure>Subset Accuracy</measure>
<measure>Macro-averaged Precision</measure>
<measure>Macro-averaged F-Measure</measure>
</measures>
</report>

</configuration>
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34 changes: 34 additions & 0 deletions dist/configurations/toML/MIMLtoML_KMT_BR.config
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<configuration>

<classifier name="miml.classifiers.miml.mimlTOml.MIMLClassifierToML">

<multiLabelClassifier name="mulan.classifier.transformation.BinaryRelevance">
<parameters>
<parameter class="weka.classifiers.Classifier" value="weka.classifiers.lazy.IBk" listOptions="-K 3 -I"/>
</parameters>
</multiLabelClassifier>
<transformationMethod name="miml.transformation.mimlTOml.KMeansTransformation"/>
</classifier>

<evaluator name="miml.evaluation.EvaluatorHoldout">
<data>
<trainFile>data/miml_birds_random_80train.arff</trainFile>
<testFile>data/miml_birds_random_20test.arff</testFile>
<xmlFile>data/miml_birds.xml</xmlFile>
</data>
</evaluator>


<report name="miml.report.BaseMIMLReport">
<fileName>results/toML/KMT_BR.csv</fileName>
<standardDeviation>false</standardDeviation>
<header>true</header>
<measures perLabel="false">
<measure>Hamming Loss</measure>
<measure>Subset Accuracy</measure>
<measure>Macro-averaged Precision</measure>
<measure>Macro-averaged F-Measure</measure>
</measures>
</report>

</configuration>
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