Hierarchical Multi-Label Software and Datasets
Funcat Datasets (Tree Structure) to be used with HMC-LMLP
Cellcycle Church Derisi Eisen Gasch1 Gasch2 Pheno Spo Expr Seq
Gene Ontology Datasets (DAG Structure) to be used with HMC-LMLP
Cellcycle Church Derisi Eisen Gasch1 Gasch2 Pheno Spo Expr Seq
Hierarchical Multi-Label Classification with Local Multi-Layer Perceptron - HMC-LMLPv1 (Cerri et. al., 2014)
Example of configuration file to be used with HMC-LMLPv1
Hierarchical Multi-Label Classification with Local Multi-Layer Perceptron - HMC-LMLP (Cerri et. al., 2016)
HMC-LMLP-Predicted source code
Example of configuration file to be used with HMC-LMLP-Predicted (Funcat)
Example of configuration file to be used with HMC-LMLP-Predicted (Gene Ontology)
Relational Hierarchical Multi-Label Classification with a Genetic Algorithm - RHMC-GA (Cerri et. al, 2014)
Example of configuration file to be used with RHMC-GA
With RHMC-GA, please use the .arff dataset files available at the KUL Machine Learning Research Group web page
Additional scripts to construct precision-recall curves and calculate the evaluation measures
statisticsHMC source code (Compute additional statistics from the results of HMC-LMLPv1)
Example of configuration file to be used with statisticsHMC
R script to create Precision-Recall curves (PR curves)
R script to calculate the weighted average of the areas under the individual PR curves
Execution instructions can be found in the source code of each script
Multi-Label Protein Subcellular Localization
Materials and results for Multi-Label Protein Subcellular Localization experiments
Self-Organizing Maps for Multi-Label Classification
Complementary Material for Self-Organizing Maps for Multi-Label Classification