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Table 4 instead of 3
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.gitignore

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src/spmf.jar
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data/TEST/TEST_CG.txt
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data/TEST/TEST_graph.txt
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data/TEST/TEST_label.txt
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data/TEST/TEST_pattern.txt
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data/FOPPA/FOPPA_CG_MONO.txt
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data/FOPPA/FOPPA_CG.txt
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data/FOPPA/FOPPA_graph.txt
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data/FOPPA/FOPPA_iso.txt
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data/FOPPA/FOPPA_label.txt
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data/FOPPA/FOPPA_mono.txt
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data/FOPPA/FOPPA_pattern.txt
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src/ECML.py
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data/PTC/PTC_CG_MONO.txt
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data/PTC/PTC_CG.txt
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data/PTC/PTC_graph.txt
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data/PTC/PTC_iso.txt
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data/PTC/PTC_label.txt
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data/PTC/PTC_mono.txt
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data/PTC/PTC_pattern.txt
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data/MUTAG/MUTAG_CG_MONO.txt
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data/MUTAG/MUTAG_CG.txt
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data/MUTAG/MUTAG_graph.txt
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data/MUTAG/MUTAG_iso.txt
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data/MUTAG/MUTAG_label.txt
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data/MUTAG/MUTAG_mono.txt
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data/MUTAG/MUTAG_pattern.txt

README.md

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3. Open the Python console.
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4. Run `EMCL.py`
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The script will compute the results of the experiments and save the results associated with Table 2,3, 5 and 6 of the paper, in the `results` folder.
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The script will compute the results of the experiments and save the results associated with Table 2, 4, 5 and 6 of the paper, in the `results` folder.
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## To Apply Pang to Other Data

data/DD/DD.zip

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data/FOPPA/FOPPA.zip

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data/MUTAG/MUTAG.zip

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data/NCI1/NCI1.zip

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data/PTC/PTC.zip

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requirements.txt

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grpcio=1.48.2=pypi_0
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h5py=3.1.0=pypi_0
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idna=3.4=pypi_0
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imbalanced-learn==0.8.1
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imblearn==0.0
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importlib-metadata=4.8.3=pypi_0
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importlib-resources=5.4.0=pypi_0
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intel-openmp=2023.0.0=h59b6b97_25923

src/ECML.py

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