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kann_class_error() doesn't work with binary cross-entropy KANN_C_CEB. With this cost, there can be multiple 1s, but kann_class_error() assumes there is only one 1.
Yep, thanks. I wasn't sure if this was intentional or not. The mnist-cnn.c example uses KANN_C_CEB with kann_train_fnn1(), which then outputs 0% class error.
kann_class_error()
always returns 0 for networks withKANN_C_CEB
cost.The text was updated successfully, but these errors were encountered: