Created
April 6, 2017 13:35
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NeuralNetConfiguration Upgrade 0.4.2 to 0.8.0
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| val conf = new NeuralNetConfiguration.Builder() | |
| .seed(seed) | |
| .iterations(1) | |
| .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT) | |
| .learningRate(0.01) | |
| .updater(Updater.NESTEROVS) | |
| .momentum(0.4) | |
| .list | |
| .layer(0, new DenseLayer.Builder().nIn(18).nOut(50) | |
| .weightInit(WeightInit.XAVIER) | |
| .activation(Activation.RELU) | |
| .build()) | |
| .layer(1, new DenseLayer.Builder().nIn(50).nOut(30) | |
| .weightInit(WeightInit.UNIFORM) // <- ? | |
| .activation(Activation.TANH) | |
| .build()) | |
| .layer(2, new DenseLayer.Builder().nIn(30).nOut(10) | |
| .weightInit(WeightInit.UNIFORM) // <- ? | |
| .activation(Activation.SIGMOID) | |
| .build()) | |
| .layer(3, new OutputLayer.Builder(LossFunctions.LossFunction.MSE) | |
| .weightInit(WeightInit.UNIFORM) // <- ? | |
| .activation(Activation.SOFTMAX) | |
| .nIn(10).nOut(3).build()) | |
| .pretrain(false).backprop(true) | |
| .build |
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| val conf = new NeuralNetConfiguration.Builder() | |
| .seed(seed) | |
| .iterations(1) | |
| .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT) | |
| .learningRate(0.01) | |
| .updater(Updater.NESTEROVS) | |
| .momentum(0.4) | |
| .list | |
| .layer(0, new DenseLayer.Builder().nIn(18).nOut(50) | |
| .weightInit(WeightInit.XAVIER) | |
| .activation("relu") | |
| .build()) | |
| .layer(1, new DenseLayer.Builder().nIn(50).nOut(30) | |
| .weightInit(WeightInit.NORMALIZED) | |
| .activation("tanh") | |
| .build()) | |
| .layer(2, new DenseLayer.Builder().nIn(30).nOut(10) | |
| .weightInit(WeightInit.NORMALIZED) | |
| .activation("sigmoid") | |
| .build()) | |
| .layer(3, new OutputLayer.Builder(LossFunctions.LossFunction.MSE) | |
| .weightInit(WeightInit.NORMALIZED) | |
| .activation("softmax") | |
| .nIn(10).nOut(3).build()) | |
| .pretrain(false).backprop(true) | |
| .build |
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