Clustering honey samples with unsupervised machine learning methods using FTIR data

Clustering honey samples with unsupervised machine learning methods using FTIR data

Abstract This study utilizes Fourier transform infrared (FTIR) data from honey samples to cluster and categorize them based on their spectral characteristics. The aim is to group similar samples together, revealing patterns and aiding in classification. The process begins by determining the number o...

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Bibliographic Details
Main Author: FATIH MEHMET AVCU
Format: Article
Language:English
Published: Academia Brasileira de Ciências 2024-03-01
Series:Anais da Academia Brasileira de Ciências
Subjects:
Fouirer transform infrared spectrophotometer
hierarchical clustering analysis
machine learning
deep Learning
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652024000100501&tlng=en

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http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652024000100501&tlng=en

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