New hybrid data mining model for prediction of Salmonella presence in agricultural waters based on ensemble feature selection and machine learning algorithms-Reference-Cited by-同舟云学术

New hybrid data mining model for prediction of Salmonella presence in agricultural waters based on ensemble feature selection and machine learning algorithms

Published:2021-04-11 Issue:4 Volume:41 Page:
ISSN:0149-6085
Container-title:Journal of Food Safety
language:en
Short-container-title:J Food Saf

Author:

Buyrukoğlu Selim¹^ORCID

Affiliation:

1. Department of Computer Engineering, Faculty of Engineering Çankırı Karatekin University Çankırı Turkey

Publisher

Wiley

Subject

Microbiology,Food Science,Parasitology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jfs.12903

Reference48 articles.

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2. Application of the Random Forest Method to Analyse Epidemiological and Phenotypic Characteristics ofSalmonella4,[5],12:i:- andSalmonellaTyphimurium Strains

3. Comparing SVM and ANN based Machine Learning Methods for Species Identification of Food Contaminating Beetles

4. Majority vote feature selection algorithm in software fault prediction

5. Artificial neural network modelling: a summary of successful applications relative to microbial water quality

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