Reaskly A cat photo classification model predicts 1 if it's a cat, and 0 if it's not a cat. For a particular photograph, the logistic regression model outputs g(z)g(z) (a number between 0 and 1). Which of these would be a reasonable criteria to decide whether to predict if it’s a cat?

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Which is an example of a classification task?

Q:

Reaskly A cat photo classification model predicts 1 if it’s a cat, and 0 if it’s not a cat. For a particular photograph, the logistic regression model outputs g(z)g(z) (a number between 0 and 1). Which of these would be a reasonable criteria to decide whether to predict if it’s a cat?

Q:

True/False? No matter what features you use (including if you use polynomial features), the decision boundary learned by logistic regression will be a linear decision boundary.

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