python - Function approximation with tensorflow, sigmoid vs relu6 -


im trying aproximate sin() function (actually can aproximate anything) tensorflow in deep neural network, has 2 layers 10 , 5 neurons each, tried many optimizers , adam seems best 1 (also found paper recommending it)

my problem if use relu6 activation function wich recommended aproximation looks https://imgur.com/a/pcsre, has lot of edges. in other hand if use sigmoid aproximation more soft less neurons looks https://imgur.com/a/gevss , don't know why fails that.

i mapped function interval [0, 1] before feeding train step.

any light on appreciated, in advance!


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