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The current implementation of the global epistasis model doesn't guarantee monotonicity between the output of the initial linear layer and the final output. In my experience, the easiest way to guarantee monotonicity is to transform the weights in the nonlinear layer to non-negative values using a softplus or something similar. (I've tried it using torch but assume it will work similarly well in keras.)
The text was updated successfully, but these errors were encountered:
The current implementation of the global epistasis model doesn't guarantee monotonicity between the output of the initial linear layer and the final output. In my experience, the easiest way to guarantee monotonicity is to transform the weights in the nonlinear layer to non-negative values using a softplus or something similar. (I've tried it using torch but assume it will work similarly well in keras.)
The text was updated successfully, but these errors were encountered: