Fig. 1From: An evaluation of machine learning classifiers for next-generation, continuous-ethogram smart trackersComparison of overall accuracies of six machine learning methods across five different datasets encompassing Common crane, Dairy cow, Griffon vulture, Roe deer and White stork, with full features sets and simplified feature sets. Mean and 95% confidence interval using 10-fold cross-validation are presented. LDA: linear discriminant analysis, DT: decision tree, SVM: support vector machine, RF: random forest, ANN: artificial neural network, XGBoost: extreme gradient boostingBack to article page