Mean and standard deviation of classifier accuracy across repeated training instances using each the three machine learning methods (compound index, pretrained CNN and trained CNN) at six different tasks. Accuracy is the proportion of one-minute recordings from the test data that were correctly classified. Methods where accuracy was reported as significantly higher by the ANOVA test are indicated in superscript next to the mean value for the respective method (A = highest group, B = second highest group, no letter = lowest group). The Random baseline accuracy indicates the expected accuracy of a model that performs random classification. N = 100 for all tasks, except the Fish diversity (Australia) and Depth (French Polynesia) tasks, where N = 32.

Mean and standard deviation of classifier accuracy across repeated training instances using each the three machine learning methods (compound index, pretrained CNN and trained CNN) at six different tasks. Accuracy is the proportion of one-minute recordings from the test data that were correctly classified. Methods where accuracy was reported as significantly higher by the ANOVA test are indicated in superscript next to the mean value for the respective method (A = highest group, B = second highest group, no letter = lowest group). The Random baseline accuracy indicates the expected accuracy of a model that performs random classification. N = 100 for all tasks, except the Fish diversity (Australia) and Depth (French Polynesia) tasks, where N = 32.