Parameters for MLP neural network classifier.
|L||Learning rate: used for weight adjustment on each iteration. (The value should be between 0 and 1.)||0.3|
|M||Momentum: used for weight adjustment during backpropagation, in order to speed up convergence and avoid local minima. (The value should be between 0 and 1.)||0.2|
|N||The number of epochs or passes through training data.||500|
|V||The percentage of the validation set from the training data.||20%|
|S||Seed for random number generator. Random numbers are used for setting initial weights for the connections between nodes. (The value should be ≥0.)||0|
|E||Threshold for consecutive errors allowed during validation testing before the neural network terminates. (The value should be >0.)||20|
|H||Number of nodes in the hidden layer which is represented as follows:|
number of hidden layers (number of neurons in each layer).
2 (11, 5)
3 (11, 5, 2)