Combining wavelength importance ranking to the random forest classifier to analyze multiclass spectral data-Reference-Cited by-同舟云学术

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Combining wavelength importance ranking to the random forest classifier to analyze multiclass spectral data

Published:2021-11 Issue: Volume:328 Page:110998
ISSN:0379-0738
Container-title:Forensic Science International
language:en
Short-container-title:Forensic Science International

Author:

de Abreu Fontes Juliana,Anzanello Michel José,Brito João B.G.,Bucco Guilherme Brandelli,Fogliatto Flavio Sanson,Puglia Fábio do Prado

Publisher

Elsevier BV

Subject

Pathology and Forensic Medicine,Law

Reference56 articles.

1. Random forest as one-class classifier and infrared spectroscopy for food adulteration detection;de Santana;Food Chem.,2019

2. WHO, Guidelines for the development of measures to combat counterfeit drugs, 1999.

3. A multivariate-based wavenumber selection method for classifying medicines into authentic or counterfeit classes;Anzanello;J. Pharm. Biomed. Anal.,2013

4. Poor quality drugs: grand challenges in high throughput detection, countrywide sampling, and forensics in developing countries;Fernandez;Analyst,2011

5. Near infrared spectroscopy and element concentration analysis for assessing yerba mate (Ilex paraguariensis) samples according to the country of origin;Kahmann;Comput. Electron. Agric.,2017

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