Week 3 "Decision Boundary"

At around 9:28 in the video of decision boundary Prof Andrew said that predicted class will 1 for the data points inside the decision boundary and outside the boundary predicted class will 0,But i think it should be otherwise


Hello @Adeel_Hasan, welcome to the community!

The previous slide shows an example that inside the ellipse the samples are predicted 0, however, in some other cases, samples inside a boundary can be for predicting 1. I explained this here, please take a look and see if it makes sense to you.

Unlike the previous slide which showed the equation with parameter values to “enforce” the class inside the ellipse to be 0, for the slide in question, Andrew didn’t show such equation, so the freedom of choice belongs to him :slight_smile: