Fig. 1. The basic structure of ANN
Fig. 2. The basic structure of RNN
Fig. 3. Types of RF
Fig. 4. Types of PRI
Fig. 5. The basic structure for LSTM model
Fig. 6. Validation accuracy by optimazation methods
Fig. 7. The validation accuracy by batch sizes
Fig. 8. The validation accuracy by dropout rates
Fig. 9. Model structures with 1 or 2 LSTM layers
Fig. 10. The validation accuracy by LSTM layers
Fig. 11. Model structure with a fully connected layer
Fig. 12. The validation accuracy by FCL
Fig. 13. The validation accuracy by feature sets
Fig. 14. Validation accuracy by learning rate decay
Table 1. Parameters
Table 2. The best accuracy by optimization methods
Table 3. The best accuracy by batch sizes
Table 4. The best accuracy by dropout rates
Table 5. The best accuracy by LSTM layers
Table 6. The best accuracy by FCL
Table 7. The best accuracy by feature sets
Table 8. The best ccuracy by learning rate decay
Table 9. Accuracy(%) of train, validation, test data
참고문헌
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