Question

When we have the hypothesis function and can measure its accuracy by the cost function how do we estimate the parameters of the hypothesis function?

Answer 1

To estimate the parameters of a hypothesis function, we can use the cost function to measure its accuracy. Gradient descent is a method which iteratively adjusts the parameters in the direction of steepest descent of the cost function to reach a minimum.

Step-by-step explanation:

When estimating the parameters of a hypothesis function, we can use the cost function to measure its accuracy. The goal is to find the parameters that minimize the cost function, indicating a good fit between the hypothesis and the data.

One way to estimate the parameters is through a method called gradient descent. This iterative algorithm adjusts the parameters in the direction of steepest descent of the cost function, gradually reaching a minimum.