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What is Machine Learning for Mud Crab Parasite Identification about?

This study explores the use of machine learning techniques to identify ectoparasite infections in the mud crab genus Scylla, focusing on five classifiers: logistic regression, k-nearest neighbors, Gaussian Naive Bayes, support vector machine, and linear discriminant analysis. The research highlights the importance of early detection of parasites to mitigate economic impacts on mud crab farming, particularly in Terengganu, Malaysia. Experimental results indicate that Gaussian Naive Bayes and linear discrimin

Author

Rendi Agus S

Language

EN