add new Activation function: selu #6969
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add new Activation function: selu #read paper to know more detail: Self-Normalizing Neural Networks:https : //arxiv.org/abs/1706.02515 #discussion: https://www.reddit.com/r/MachineLearning/comments/6g5tg1/r_selfnormalizing_neural_networks_improved_elu/ usage: just like relu: model.add(Dense(64, activation='relu')) ---model.add(Dense(64, activation='selu'))
add new Activation function: selu #read paper to know more detail: Self-Normalizing Neural Networks:https : //arxiv.org/abs/1706.02515 #discussion: https://www.reddit.com/r/MachineLearning/comments/6g5tg1/r_selfnormalizing_neural_networks_improved_elu/ usage: just like relu: model.add(Dense(64, activation='relu')) ---model.add(Dense(64, activation='selu'))
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forget to add some test in backend_test.py , PR closed. |
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@cc786537662 You might want to look at #6969 before you add more changes |
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nice job, that covers my PR, |
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Yeah that's what I meant thanks thanks |
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add new Activation function : selu
#read paper to know more detail:
Self-Normalizing Neural Networks:https : //arxiv.org/abs/1706.02515
#discussion:
https://www.reddit.com/r/MachineLearning/comments/6g5tg1/r_selfnormalizing_neural_networks_improved_elu/
#usage:
just like relu:
model.add(Dense(64, activation='relu'))
---model.add(Dense(64, activation='selu'))
experiment on mnist：（run keras-master\examples\mnist_cnn.py）：
with relu：
Test loss: 0.025632923909
Test accuracy: 0.9915
replace relu in network with selu:
Test loss: 0.052635348707
Test accuracy: 0.9837