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Table 4 Hyperparameters and training time of CNN models

From: Convolutional neural network models for cancer type prediction based on gene expression

 TrainingTesting 
DL modelaNumber of parametersLossAccuracyLossAccuracybTimec (seconds)
1D-CNN211,4890.010.99710.17690.956780.3
2D-Vanilla-CNN1,420,7370.0070.99810.17780.955794
2D-Hybrid-CNN362,1770.01490.9960.15860.958280.8
2D-3Layer-CNN26,211,2330.51490.96540.68750.9184214.6
2D-3Layer-CNN (with patience = 10) 0.19760.98690.39140.9419379.17
  1. aEarly stopping is used for all models (all with patience = 4, except for the last model)
  2. bResults of 5-fold cross-validations
  3. cAll models were trained using a Linux server with Xeon 8176 CPU @2.1GHz, with 4 × 28 cores