normalization/automodel/ deep learning
Hello I'm a beginner using rapidminer and I normalized my data in 2 different ways, but when I use "Automodel" I get the same results.
I'm using deep learning and I know that this method (in rapidminer) applies standardization by default when automodeling. I' m trying to do a regression and no matter how I introduce the dataset to train my model (without normalization, z transformation, range transformation), I always get the same results.
So, I want to know why this happen, any guidance will be helpful! Thanks
(maybe it is some Deep learning feature I'm ignoring)
(by the way, I love the platform)
I'm using deep learning and I know that this method (in rapidminer) applies standardization by default when automodeling. I' m trying to do a regression and no matter how I introduce the dataset to train my model (without normalization, z transformation, range transformation), I always get the same results.
So, I want to know why this happen, any guidance will be helpful! Thanks
(maybe it is some Deep learning feature I'm ignoring)
(by the way, I love the platform)