Decision Boundary
Learn about the concept of decision boundary.
Decision boundary for logistic regression
We have just figured out that whenever z equals zero, we are in the decision boundary. But z is given by a linear combination of features x1 and x2. If we work out some basic operations, we arrive at:
Given our model (b, w1, and w2), for any value of the first feature (x1), we can compute the corresponding value of the second feature (x2) that sits exactly at the decision boundary.
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