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Table 2 Parameter Values for Scalable DNN-Based Indoor Localization

From: A scalable deep neural network architecture for multi-building and multi-floor indoor localization based on Wi-Fi fingerprinting

DNN parameter Value
Ratio of training data to overall data 0.90
Number of Epochs 20
Batch size 10
SAE hidden layers 256-128-256
SAE activation Rectified Linear (ReLU)
SAE Optimizer ADAM [25]
SAE loss Mean Squared Error (MSE)
Classifier hidden layers 64-128
Classifier activation ReLU
Classifier optimizer ADAM
Classifier loss Binary Crossentropy
Classifier dropout rate 0.20