Fig. 12From: Machine learning for high-throughput field phenotyping and image processing provides insight into the association of above and below-ground traits in cassava (Manihot esculenta Crantz)Plots based on regression methods, validation dataset on the left and test dataset on the right. a RF parameters (max_features:4, trees: 100). b SVM parameter (C:2.1, kernel:”rbf“). c kNN parameters (algorithm: ball_tree, K: 38, weights: uniform). d ANNBack to article page