a$.$ We have collected $N$ data samples. Each sample has two features denoted as

$x=\{x{1}_n,x{2}_n\}(n=1,$dots,$N),$ and the corresponding outcome $Y=\{y_n\}$ is either $0$ or $1.$

You are asked to use Logistic Regression to build a binary classification model. The

logistic function for this task is given below. $(1)$ Write a loss function that is

applicable to this task and explain the meaning of each variable in your loss

function. $(2)$ State the intrinsic parameters to be estimated by optimising the loss

function.

Logistic function: $P(x)=\frac{1}{1+e^{-(w0+w1x1+w2x2)}}$