PRINCIPAL COMPONENT ANALYSIS (PCA) PARA A AVALIAÇÃO DE DADOS QUÍMICOS E GERAÇÃO DE HEAT MAPS: UM TUTORIAL
PRINCIPAL COMPONENT ANALYSIS (PCA) FOR CHEMICAL DATA EVALUATION AND HEAT MAPS PREPARATION: A TUTORIAL. This tutorial shows a step-by-step guide on handling big datasets using principal component analysis (PCA). A dataset of chemical elements’ concentration, emission spectrum, and energy-dispersive X...
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| Format: | Article |
| Language: | English |
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Sociedade Brasileira de Química
2023-08-01
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| Series: | Química Nova |
| Subjects: | |
| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422023000700747&lng=pt&tlng=pt |
| _version_ | 1797733715780042752 |
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| author | Dennis da Silva Ferreira Leticia da Silva Rodrigues Fabiola Manhas Verbi Pereira Edenir Rodrigues Pereira Filho |
| author_facet | Dennis da Silva Ferreira Leticia da Silva Rodrigues Fabiola Manhas Verbi Pereira Edenir Rodrigues Pereira Filho |
| author_sort | Dennis da Silva Ferreira |
| collection | DOAJ |
| description | PRINCIPAL COMPONENT ANALYSIS (PCA) FOR CHEMICAL DATA EVALUATION AND HEAT MAPS PREPARATION: A TUTORIAL. This tutorial shows a step-by-step guide on handling big datasets using principal component analysis (PCA). A dataset of chemical elements’ concentration, emission spectrum, and energy-dispersive X-ray fluorescence (EDXRF) of e-waste were used as examples. Five routines were proposed to apply data processing and PCA calculation focusing data from laser-induced breakdown spectroscopy (LIBS), EDXRF, and heat maps preparation. These routines can be used in various softwares such as MatLab, Octave, R, and Python. PCA was applied in three examples; the first was for concentrations, and the other two were for spectra. An example of heat maps assembling a hyperspectral image of a printed circuit was also described. In addition, a playlist was created on YouTube using the available examples. Therefore, with this tutorial, it may be possible to learn how to deal with a large volume of data by applying PCA. The authors hope to contribute to those researching in the area. |
| first_indexed | 2024-03-12T12:32:10Z |
| format | Article |
| id | doaj.art-c422cf5761ba481a82b5baba9280a20e |
| institution | Directory Open Access Journal |
| issn | 1678-7064 |
| language | English |
| last_indexed | 2024-03-12T12:32:10Z |
| publishDate | 2023-08-01 |
| publisher | Sociedade Brasileira de Química |
| record_format | Article |
| series | Química Nova |
| spelling | doaj.art-c422cf5761ba481a82b5baba9280a20e2023-08-29T07:45:32ZengSociedade Brasileira de QuímicaQuímica Nova1678-70642023-08-0146774775410.21577/0100-4042.20230030PRINCIPAL COMPONENT ANALYSIS (PCA) PARA A AVALIAÇÃO DE DADOS QUÍMICOS E GERAÇÃO DE HEAT MAPS: UM TUTORIALDennis da Silva Ferreirahttps://orcid.org/0000-0003-1554-8901Leticia da Silva Rodrigueshttps://orcid.org/0000-0002-9601-1323Fabiola Manhas Verbi Pereirahttps://orcid.org/0000-0002-8117-2108Edenir Rodrigues Pereira Filhohttps://orcid.org/0000-0003-0608-0278PRINCIPAL COMPONENT ANALYSIS (PCA) FOR CHEMICAL DATA EVALUATION AND HEAT MAPS PREPARATION: A TUTORIAL. This tutorial shows a step-by-step guide on handling big datasets using principal component analysis (PCA). A dataset of chemical elements’ concentration, emission spectrum, and energy-dispersive X-ray fluorescence (EDXRF) of e-waste were used as examples. Five routines were proposed to apply data processing and PCA calculation focusing data from laser-induced breakdown spectroscopy (LIBS), EDXRF, and heat maps preparation. These routines can be used in various softwares such as MatLab, Octave, R, and Python. PCA was applied in three examples; the first was for concentrations, and the other two were for spectra. An example of heat maps assembling a hyperspectral image of a printed circuit was also described. In addition, a playlist was created on YouTube using the available examples. Therefore, with this tutorial, it may be possible to learn how to deal with a large volume of data by applying PCA. The authors hope to contribute to those researching in the area.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422023000700747&lng=pt&tlng=ptexploratory analysisdata miningdata visualizationdirect solid sample analysislaserX-ray fluorescence |
| spellingShingle | Dennis da Silva Ferreira Leticia da Silva Rodrigues Fabiola Manhas Verbi Pereira Edenir Rodrigues Pereira Filho PRINCIPAL COMPONENT ANALYSIS (PCA) PARA A AVALIAÇÃO DE DADOS QUÍMICOS E GERAÇÃO DE HEAT MAPS: UM TUTORIAL Química Nova exploratory analysis data mining data visualization direct solid sample analysis laser X-ray fluorescence |
| title | PRINCIPAL COMPONENT ANALYSIS (PCA) PARA A AVALIAÇÃO DE DADOS QUÍMICOS E GERAÇÃO DE HEAT MAPS: UM TUTORIAL |
| title_full | PRINCIPAL COMPONENT ANALYSIS (PCA) PARA A AVALIAÇÃO DE DADOS QUÍMICOS E GERAÇÃO DE HEAT MAPS: UM TUTORIAL |
| title_fullStr | PRINCIPAL COMPONENT ANALYSIS (PCA) PARA A AVALIAÇÃO DE DADOS QUÍMICOS E GERAÇÃO DE HEAT MAPS: UM TUTORIAL |
| title_full_unstemmed | PRINCIPAL COMPONENT ANALYSIS (PCA) PARA A AVALIAÇÃO DE DADOS QUÍMICOS E GERAÇÃO DE HEAT MAPS: UM TUTORIAL |
| title_short | PRINCIPAL COMPONENT ANALYSIS (PCA) PARA A AVALIAÇÃO DE DADOS QUÍMICOS E GERAÇÃO DE HEAT MAPS: UM TUTORIAL |
| title_sort | principal component analysis pca para a avaliacao de dados quimicos e geracao de heat maps um tutorial |
| topic | exploratory analysis data mining data visualization direct solid sample analysis laser X-ray fluorescence |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422023000700747&lng=pt&tlng=pt |
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