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Given a dataset of n features, we want to learn a function ℝⁿ ⟶ ℝ that fits the data without overfitting it. Fixing the method of training the model, the free parameter that decides what our function will be is the architecture of the network. The model space has networks with n inputs and one output.
The text was updated successfully, but these errors were encountered:
Given a dataset of
n
features, we want to learn a functionℝⁿ ⟶ ℝ
that fits the data without overfitting it. Fixing the method of training the model, the free parameter that decides what our function will be is the architecture of the network. The model space has networks withn
inputs and one output.The text was updated successfully, but these errors were encountered: