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Deep Learning for Population Genetic Inference

Table 5

Relative error on the test dataset, for a deep network with 6 hidden layers.

For the results in the first row, the weights of the entire network were initialized randomly, then optimized. In the second row, the weights were initialized using autoencoders for each layer. The positive impact of unsupervised pretraining is clear; random initialization causes the optimization to get stuck in a local minima.

Table 5