data_mining:neural_network:initialization

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NN initialization

Weights need to be randomly initialized. For bias zero is ok.

If weights are zero: in backprop ⇒ $dz_{1,2}$ are the same. Hidden units would compute same function (= are symmetric).

Solution: $W^{[i]}=np.random.randn((2,2)) * 0.01$

$0.01$ because else we would end up at ends of activation function values (and slopes would be small).

  • data_mining/neural_network/initialization.1503175053.txt.gz
  • Last modified: 2017/08/19 22:37
  • by phreazer