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for layer in model.children():
if hasattr(layer, 'reset_parameters'):
layer.reset_parameters()
For the first fold/split the result of c-index is always low and then after couple of SEEDS the performance kept growing up. Hence, i believe the training model was not re-initialized after training one fold.
Does anyone know how to fix this issue and reset/re-initialize model for every fold.
Thank you in advance.
The text was updated successfully, but these errors were encountered:
Hi,
I was working on cross validation/ splitting data using different seed points and then train a PyCOX model before averaging the result.
``for seed in SEEDS:
there are some steps here and I posted the required sections.
log = model.fit(X_train, y_train, batch_size, epochs, callbacks,verbose, val_data=val, val_batch_size=batch_size)
##added the following to reset the parameters
for layer in model.children():
if hasattr(layer, 'reset_parameters'):
layer.reset_parameters()
For the first fold/split the result of c-index is always low and then after couple of SEEDS the performance kept growing up. Hence, i believe the training model was not re-initialized after training one fold.
Does anyone know how to fix this issue and reset/re-initialize model for every fold.
Thank you in advance.
The text was updated successfully, but these errors were encountered: