Comparison of random forest, support vector machine and back propagation neural network for electronic tongue data classification: Application to the recognition of orange beverage and Chinese vinegar

By Miao Liu, Mingjun Wang, Jun Wang, Duo Li. 2013

311 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Molecular Biology, Nutrition and Dietetics

View Paper: https://www.semanticscholar.org/paper/c6957e1e1c241e1e116a0856273f70c893a47971

How researchers see this paper

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In Molecular Biology

1. Harsurinder Kaur
2. Husanbir Singh Pannu
3. Avleen Kaur Malhi
4. Lei Wang

Citations in the corpus

• A Systematic Review on Imbalanced Data Challenges in Machine Learning (2019, methodology): “Liu et al. (2013) proposed a technique of data processing for electronic tongue and the results of accuracy were compared with other classification algorithms to detect the samples of orange beverage and chinese vinegar.”
• Comparison of random forest, artificial neural networks and support vector machine for intelligent diagnosis of rotating machinery (2018, background): “In recent years, random forest has drawn wide attention in the fields of E-tongue (Liu et al., 2013), acoustic emission (Morizet et al.”