Machine learning approach for automatic recognition of tomato-pollinating bees based on their buzzing-sounds
Table 4
Confusion matrix with the best performance for bee buzzing-sounds classification at genus-level using MFCC features (flight with SVM classifier, MacF1 = 60.20% and Acc = 64.15%).
The numbers in the matrix correspond to correctly (diagonal elements, bold) and incorrectly (out-of-diagonal elements) recognized samples in the data set. The best parameters of this classification were C = 10, decision_function_shape = “ovo”, gamma = 0.01, kernel = “rbf”.