Random Forest, Artificial Neural Network, and Support Vector Machine Models for Honey Classification
Different separated protein fractions by the electrophoretic method in polyacrylamide gel were used to classify two different types of honeys, Galician honeys and commercial honeys produced and packaged outside of Galicia. Random forest, artificial neural network, and support vector machine models w...
Main Authors: | Cecilia Martinez-Castillo, Gonzalo Astray, Juan Carlos Mejuto, Jesus Simal-Gandara |
---|---|
Format: | Article |
Language: | English |
Published: |
Atlantis Press
2019-10-01
|
Series: | eFood |
Subjects: | |
Online Access: | https://www.atlantis-press.com/article/125919278/view |
Similar Items
-
Honey Volatiles as a Fingerprint for Botanical Origin—A Review on their Occurrence on Monofloral Honeys
by: Alexandra M. Machado, et al.
Published: (2020-01-01) -
Botanical origin and characterization of monofloral honeys in Southwestern forest of Ethiopia
by: Admassu Addi, et al.
Published: (2021-09-01) -
Analysis of organic molecules, physicochemical parameters, and pollen as indicators for authenticity, botanical origin, type and quality of honey samples examined
by: O. Fuentes Molina, et al.
Published: (2020-01-01) -
PHYSICO-CHEMICAL PARAMETERS OF ROMANIAN RASPBERRY HONEY
by: Daniela PAULIUC, et al.
Published: (2019-12-01) -
The monoclonal antibody for discrimination of natural honey against artificial honey
by: Taeri Joe, et al.
Published: (2018-11-01)