Logistic Regression - Hypothesis Representation

Logistic Regression - Hypothesis Representation

Linear regression: $h_\theta(x) = \theta^{T}x$

Want $0 <= h_\theta(x) <= 1$
Logistic regression: $h_\theta(x) = g(\theta^{T}x)$ where $g(z) = \frac{1}{1 + e^{-z}}$ (sigmoid/logistic function)

Resources:
- https://www.coursera.org/learn/machine-learning/supplement/AqSH6/hypothesis-representation