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LSTM and RNN to Predict COVID Cases: Lethality’s and Tests in GCC Nations and India
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Sulthana A. Razia, Jovith Arokiaraj, A. K. Jaithunbi
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Table 4. LSTM error table
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Adam Classifier: RNN using LSTM Country: India 4 hidden layer, each with 10 units. A dropout of 0.2 in each layer. Output layer with 1 unit Calculated: mean_squared_error | epoch 1 | Total Cases | Total Deaths | Total tests | epoch 2 | 0.0463 | 0.0562 | 0.0334 | epoch 3 | 0.0378 | 0.0498 | 0.0310 | epoch 4 | 0.0361 | 0.0455 | 0.0298 | epoch 5 | 0.0339 | 0.0344 | 0.0251 | epoch 6 | 0.0325 | 0.0321 | 0.0201 | epoch 7 | 0.0263 | 0.0314 | 0.0098 | epoch 8 | 0.0224 | 0.0214 | 0.0077 | epoch 9 | 0.0131 | 0.0121 | 0.0052 | epoch 10 | 0.0057 | 0.0088 | 0.0001 |
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