Create setting for RNN model with python

setRNNTorch(hidden_size = c(50, 100), epochs = c(20, 50), seed = 0,
class_weight = 0, type = "RNN")

Arguments

hidden_size The hidden size The number of epochs A seed for the model The class weight used for imbalanced data: 0: Inverse ratio between positives and negatives -1: Focal loss It can be normal 'RNN', 'BiRNN' (bidirectional RNN) and 'GRU'

Examples

# NOT RUN {
model.rnnTorch <- setRNNTorch()
# }