Create setting for DeepNN model
setDeepNN( units = list(c(128, 64), 128), layer_dropout = c(0.2), lr = c(1e-04), decay = c(1e-05), outcome_weight = c(1), batch_size = c(100), epochs = c(100), seed = NULL )
units | The number of units of the deep network - as a list of vectors |
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layer_dropout | The layer dropout rate (regularisation) |
lr | Learning rate |
decay | Learning rate decay over each update. |
outcome_weight | The weight of the outcome class in the loss function |
batch_size | The number of data points to use per training batch |
epochs | Number of times to iterate over dataset |
seed | Random seed used by deep learning model |
if (FALSE) { model <- setDeepNN() }