Elaine Cecília Gatto's repositories
Multi-Label-Friedman-Nemenyi
Compute Friedman and Nemenyi Statistical Tests for Multilabel Classification
Bracis2023
Repository of the paper "Community Detection Methods for Multi-Label Classification" publish in BRACIS 2023
Cheat-Sheet-Statistic-R-Python
This repository contains the concepts, equations and commands to do statistical analysis with R and Python
jaccard
This code generate partitions for a multilabel dataset using the Jaccard Index similarity measure. We use HCLUST with 6 linkage metrics to generate several partitions. You may build the partition with the highest coefficient. This code also provide an analysis about the partitioning.
MultilabelPerformanceEvaluationMeasures
This code shows how to compute the measures of multi-label classification hand in hand.
rogers
This code generate partitions for a multilabel dataset using the Rogers-Tanimoto similarity measure. We use HCLUST with 6 linkage metrics to generate several partitions. You may build the partition with the highest coefficient. This code also provide an analysis about the partitioning.
Win-Tie-Loss
One-versus-all comparison. Count how many times your method (algorithm) obtained a better result when compared to all other methods (algorithms) in your experiment.
HPML-KAIS
Repository for the paper "Multi-Label Classification with Label Clusters"
BellPartitionsMultiLabel
This code generates partitions based on bell numbers for multilabel classification.
Best-Partition-Kohonen-MaF1-Clus
This code is part of my doctoral research. The aim choose the best partition generated.
Best-Partition-Kohonen-MiF1-Clus
This code is part of my doctoral research. The aim choose the best partition generated.
Best-Partition-MaF1-Clus
This code is part of my PhD research. This code select the best partition using the CLUS framework. We choose the partition with the best Macro-F1.
Best-Partition-MiF1-Clus
This code is part of my Ph.D. research. This code selects the best partition using the CLUS framework. We choose the partition with the best Micro-F1.
Exhaustive-MaF1-Clus
This code is part of my doctoral research. The aim is to build, validate and test all possible partitions for multilabel classification using CLUS framework.
Exhaustive-MiF1-Clus
This code is part of my doctoral research. The aim is to build, validate and test all possible partitions for multilabel classification using CLUS framework.
Generate-Partitions-Jaccard
This code is part of my doctoral research. The aim is to generate partitions from the Jaccard index for multilabel classification.
Generate-Partitions-Kohonen
This code is part of my PhD research. This code generate hybrid partitions using Kohonen to modeling the labels correlations, and HClust to partitioning the label space.
Generate-Partitions-Random2
This code is part of my doctoral research. The aim is to generate a specific version of random partitions for multilabel classification.
Generate-Partitions-Rogers
This code is part of my doctoral research. The aim is to generate partitions using Rogers-Tanimoto similarity measure.
HPML-Chains
This code is a part of my doctoral research at PPG-CC/DC/UFSCar in colaboration with Ku Leuven in Belgium.
LH_CD_ElaineGatto
INDICIUM - Processo Seletivo - Lighthouse Programa De Formação Em Dados - Remoto
Oracle-Clus
This code is part of my doctoral research. It's oracle experimentation of Bell Partitions using the CLUS framework.
Pair-Comparison
One-to-one comparison. Count how many datasets your method (algorithm) obtained the best result when compared to other method (or methods) in your experiment.
Test-Best-Partition-MaF1-Clus
This code is part of my Ph.D. research. Test the best hybrid partition chosen with Macro-F1 criteria using Clus framework.
Test-Best-Partition-MiF1-Clus
This code is part of my Ph.D. research. Test the best hybrid partition chosen with Micro-F1 criteria using Clus framework.
Test-Best-Partition-Silhouette-Clus
This code is part of my Ph.D. research. Test the best hybrid partitions with Clus framework.