APLICATIVO GAMMA-GUI: UMA INTERFACE GRÁFICA AMIGÁVEL PARA ANÁLISE EXPLORATÓRIA DE DADOS NO MATLAB

GAMMA-GUI APP: A USER-FRIENDLY GRAPHICAL INTERFACE FOR EXPLORATORY DATA ANALYSIS IN MATLAB. In this work, we continue our series of tutorial articles published in the Química Nova exploring different features of the GAMMA-GUI app (Grupo de Análise Multivariada em Matrizes Alimentares), a user-friendly interface for the multivariate analysis in Matlab®. This time, we demonstrate five types of exploratory data analysis (unsupervised learning), complemented by video demonstrations on our YouTube channel. Applications consist of demonstration with: (i) principal component analysis (PCA); (ii) self-organizing maps (SOM); (iii) hierarchical cluster analysis (HCA); (iv) k-means, and (v) common dimensions analysis (ComDim). Additionally, a demonstration of descriptive statistics with Tukey HSD (honest significant difference) has been included in this tutorial. Suggestions for improvements or new ideas for the app are welcome and can be directed to the developers.

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Publication Details

Journal
Química Nova
Published
2025-01-01
DOI
https://doi.org/10.21577/0100-4042.20250206
Primary Topic
Water Quality Monitoring Technologies
Type
article
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article

APLICATIVO GAMMA-GUI: UMA INTERFACE GRÁFICA AMIGÁVEL PARA ANÁLISE EXPLORATÓRIA DE DADOS NO MATLAB

Jelmir Craveiro de Andrade, Evandro Bona, Diego Galvan, Patrícia Casarin et al.
Química Nova
Water Quality Monitoring Technologies
article

APLICATIVO GAMMA-GUI: UMA INTERFACE GRÁFICA AMIGÁVEL PARA ANÁLISE EXPLORATÓRIA DE DADOS NO MATLAB

Jelmir Craveiro de Andrade, Evandro Bona, Diego Galvan, Patrícia Casarin, Tácito Lucena Conte, João Marcos Marques Liduário
article en

Abstract

GAMMA-GUI APP: A USER-FRIENDLY GRAPHICAL INTERFACE FOR EXPLORATORY DATA ANALYSIS IN MATLAB. In this work, we continue our series of tutorial articles published in the Química Nova exploring different features of the GAMMA-GUI app (Grupo de Análise Multivariada em Matrizes Alimentares), a user-friendly interface for the multivariate analysis in Matlab®. This time, we demonstrate five types of exploratory data analysis (unsupervised learning), complemented by video demonstrations on our YouTube channel. Applications consist of demonstration with: (i) principal component analysis (PCA); (ii) self-organizing maps (SOM); (iii) hierarchical cluster analysis (HCA); (iv) k-means, and (v) common dimensions analysis (ComDim). Additionally, a demonstration of descriptive statistics with Tukey HSD (honest significant difference) has been included in this tutorial. Suggestions for improvements or new ideas for the app are welcome and can be directed to the developers.

Química Nova
Openalex Percentile: Top 79%
Water Quality Monitoring Technologies
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APLICATIVO GAMMA-GUI: UMA INTERFACE GRÁFICA AMIGÁVEL PARA ANÁLISE EXPLORATÓRIA DE DADOS NO MATLAB — Jelmir Craveiro de Andrade, Evandro Bona, et al. · Química Nova (2025) | TGRS Research Map | TGRS