On Tue, May 23, 2017 at 4:51 AM, Hideki Kato <hideki_ka...@ybb.ne.jp> wrote:
> (3) CNN cannot learn exclusive-or function due to the ReLU > activation function, instead of traditional sigmoid (tangent > hyperbolic). CNN is good at approximating continuous (analog) > functions but Boolean (digital) ones. > Oh, not this nonsense with the XOR function again. You can see a neural network with ReLU activation function learning XOR right here: http://playground.tensorflow.org/#activation=relu& batchSize=10&dataset=xor®Dataset=reg-plane&learningRate=0.01& regularizationRate=0&noise=0&networkShape=4,4&seed=0.96791& showTestData=false&discretize=false&percTrainData=50&x=true& y=true&xTimesY=false&xSquared=false&ySquared=false&cosX= false&sinX=false&cosY=false&sinY=false&collectStats=false& problem=classification&initZero=false&hideText=false Enjoy, Álvaro.
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