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Table 2 Hyperparameters Configuration

From: Ecosense: a revolution in urban air quality forecasting for smart cities

Hyperparameter

Description

Value

Number of LSTM Layers

Number of stacked LSTM layers in the model

25

Number of Units per Layer

Number of LSTM units per layer

25

Batch Size

Number of samples per gradient update

64

Learning Rate

Step size for weight updates

0.01

Dropout Rate

Fraction of input units to drop during training

0.03

Recurrent Dropout Rate

Fraction of recurrent units to drop during training

0.05

Sequence Length

Number of time steps in each input sequence

12

Optimizer

Algorithm used to optimize the loss function

Adam

Activation Function

Function used to introduce non-linearity

Softmax