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Table 1 LSTM Network configurations

From: Prediction and detection of freezing of gait in Parkinson’s disease from plantar pressure data using long short-term memory neural-networks

Hyperparameter

Values tested

Number of LSTM layers

1, 2, 3, 4, 5

Number of units in each LSTM layer

16, 32, 64

Constant learning rate

0.1, 0.01, 0.001, 0.0001

Learning rate decay with a decay rate

(decay rate, initial learning rate)

(0.5, 0.005), (0.75, 0.001)

Learning rate decreases in discrete steps

(initial learning rate)

Decreases to half every 5 epochs (0.01)