Abstract:
Major animal diseases pose a great threat to animal husbandry and human beings. With the deepening of
globalization and the abundance of data resources, the prediction and analysis of animal diseases by using big data are
becoming more and more important. The focus of machine learning is to make computers learn how to learn from data
and use the learned experience to analyze and predict. Firstly, this paper introduces the animal epidemic situation and
machine learning. Then it briefly introduces the application of machine learning in animal disease analysis and prediction.
Machine learning is mainly divided into supervised learning and unsupervised learning. Supervised learning includes
support vector machines, naive bayes, decision trees, random forests, logistic regression, artificial neural networks, deep
learning, and AdaBoost. Unsupervised learning has maximum expectation algorithm, principal component analysis
hierarchical clustering algorithm and maxent. Through the discussion of this paper, people have a clearer concept of
machine learning and understand its application prospect in animal diseases.
Assessment of animal diseases caused by bacteria resistant to antimicrobials: rabbits
