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Elaine Cecília Gatto (@cissagatto)

cissagatto

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MIPS32BitsCheatsheet

Cheatsheet completinha do MIPS 32 bits - MIPS Technologies

CrossValidationMultiLabel

A code to execute and save cross-validation in multilabel classification

R_MultiLabel_Csv2Arff

This code converts CSV file in an ARFF file correctly for a multi-label dataset

cissagatto

HPML-J

This code is a part of my doctoral research at PPG-CC/DC/UFSCar. HPML-J is the name of the first experiment carried out: Hybrid Partitions for Multi-Label Classification with index Jaccard.

HPML-Set-Up-5

Random3-ECC

Random3-Clus

Global-Clus-TVT

This code is part of my doctoral research. The aim is to build, validate and test global partitions for multilabel classification using the CLUS framework.

CheatSheetPipelineMIPS32Bits

Cheat Sheet Pipeline MIPS 32 Bits

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.

Generate-Random-Communities

Building-a-container-with-APPTAINER-to-run-R-scripts-on-a-cluster-with-SLURM

Building a container with APPTAINER to run R scripts on a cluster with SLURM.

Generate-Partitions-Random1

This code is part of my doctoral research. The aim is to generate a specific version of random partitions for multilabel classification.

Best-Partition-MacroF1

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.

Ensemble-Classifier-Chains

This code is part of my Ph.D. research. The R script runs in parallel the ECC made in python.

R-CLUS-HMC

This code executes the CLUS algorithm in an R script.

HPML-Set-Up-4

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.

Exhaustive-Silhouette-Clus

Propriedades-Multirrotulo

MIPS32BitsExemploCompleto

Um exemplo completinho de Exemplo MIPS: programa principal, funções, vetores, arrays, if, for, while, recursividade

Exhaustive-Silhouette-ECC

Best-Partition-Kohonen-MaF1-ECC

Bracis2023

Repository of the paper "Community Detection Methods for Multi-Label Classification" publish in BRACIS 2023

HPML-Set-Up-6

Best-Partition-Kohonen-MiF1-ECC

Cheat-Sheet-Statistic-R-Python

This repository contains the concepts, equations and commands to do statistical analysis with R and Python

Best-Partition-Silhouete

This code is part of my PhD research. This code select the best partition using the silhouete coefficient.

Trabalho3_AP

Trabalho 3 da disciplina de Aprendizado de Máquina. Prof. Dr. Diego, Departamento de Computação, UFSCar

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.

Test-Best-Partition-MacroF1-TT

This code is part of my Ph.D. research. Test the best hybrid partitions with Clus framework.

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.

MesaRedona-DGIA-CPBR16

Repositório da mesa resonda sobre Discriminação de Gênero e Inteligência Artificial

Bootcamp-Data-Analytics-WoMakersCode-2024

HPML

This repository hold all experiments conducted during my PhD (2019-2023). HPML means "Hybrid Partitions for Multi-Label Classification". SET-UP-1