Complex nonlinear decision boundary

Hello,
Andrew said in the week 3 decision boundary titled video that y = 1 is inside the boundary in the case of a complex nonlinear boundary. I couldn’t understand any specific reason behind this.
Can anyone help me to understand this? I attached the screenshot.

The video can be found at:
https://www.coursera.org/learn/machine-learning/lecture/qrxwU/decision-boundary

Where the 1’s and 0’s lie depends entirely on the signs and magnitudes of the weights.

The sketch in the lecture is illustrating that a model with lots of polynomial terms can create a complex boundary. It’s not necessarily about which side of the boundary has the 1’s.

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Thanks a lot!