Hitachi_Influenza_RNN_All

Posted by not set

Copy the project to Neural Network Console Cloud

Network Architecture : Main

Type	Value
Output	46,172
CostParameter	673,201
CostAdd	7,651
CostMultiply	15,300
CostMultiplyAdd	665,550
CostDivision	0
CostExp	0
CostIf	7,650

Training Procedure : Optimizer

Optimize network “Main” using “Training” dataset.

• Batch size : 32
• Solver : Adam
• Learning rate(Alpha) : 0.001
• decayed every 1 iteration using an exponential rate of 0.1 .
• Beta1 : 0.9
• Beta2 : 0.999
• Epsilon : 1e-08
• Weight decay is not applied.

Experimental Result : Learning Curve

Experimental Result : Evaluation

Evaluate network “MainRuntime” using “Validation” dataset.

Variable : y

• Accuracy : 0.8048780487804879
• Avg.Precision : 0.6
• Avg.Recall : 0.8974358974358974
• Avg.F-Measures : 0.6095238095238096

References

• Sony Corporation. Neural Network Console : Not just train and evaluate. You can design neural networks with fast and intuitive GUI. https://dl.sony.com/
• Sony Corporation. Neural Network Libraries : An open source software to make research, development and implementation of neural network more efficient. https://nnabla.org/
• LeakyReLU – Andrew L. Maas, Awni Y. Hannun, Andrew Y. Ng. Rectifier Nonlinearities Improve Neural Network Acoustic Models. https://ai.stanford.edu/~amaas/papers/relu_hybrid_icml2013_final.pdf
• Adam – Kingma and Ba, Adam: A Method for Stochastic Optimization. https://arxiv.org/abs/1412.6980