1 Let us consider the problem of nearest-mean classifier. Suppose we are given N training samples(x1,Y1), ..., (XN,YN) from two classes with yn E {+1, –1}. We saw in lecture 2 that we can decide alabel for a test vector x as g(x) = sign(w'x+b), where w =2(u+ - µ-) and b = ||µ- ||3 – ||4+|3.H+ is a mean vector for samples in the +ve class and u_ is a mean vector for samples the -ve class.Show that w'x+b = E=1 an(Xn, x) + b and calculate the values of the an.

In this problem, we delve into the Nearest-Mean Classifier, a method for deciding the label of a…

Let us consider the problem of nearest-mean classifier. Suppose we are given N training samples (x₁, y₁),..., (XN, YN) from two classes with yn € {+1, -1}. We saw in lecture 2 that we can decide a label for a test vector x as g(x) = sign (w²x + b), where w = 2(µ+ − µ-) and b = ||µ–||²3 − ||µ+||³2. - μ+ is a mean vector for samples in the +ve class and p_ is a mean vector for samples the -ve class. Show that w²x + b = 1 an(xn, x) + b and calculate the values of the an.

Let us consider the problem of nearest-mean classifier. Suppose we are given N training samples (x₁, y₁),..., (XN, YN) from two classes with yn € {+1, -1}. We saw in lecture 2 that we can decide a label for a test vector x as g(x) = sign (w²x + b), where w = 2(µ+ − µ-) and b = ||µ–||²3 − ||µ+||³2. - μ+ is a mean vector for samples in the +ve class and p_ is a mean vector for samples the -ve class. Show that w²x + b = 1 an(xn, x) + b and calculate the values of the an.