Quote:
Originally Posted by itooam
from the lectures I understood Eout(g) to be the "true" error (if you had access to the full population of data). In reality, when we are applying a machine learning technique, we do so because we have limited data and therefore I fail to understand how this formula can be applied?
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In a practical machine learning situation, we don't have
but we estimate it using a test set (set of fresh points) as we have done in Homework 1 with the perceptron. The accuracy of that estimate will be discussed in detail when we talk about validation.