Fig. 7From: Machine-learning strategies for testing patterns of morphological variation in small samples: sexual dimorphism in gray wolf (Canis lupus) craniaEmbedded LeNet-5 training summary for the dorso-ventral crania dataset. Note the length of the training cycle, the steady improvement in the loss ratio during the whole of the training interval, and the distinct reduction in loss improvement as the point of convergence is reached. The entire training cycle took 21 s of CPU time to completeBack to article page