from a machine learning class

1. QuESTION 1: LIKELIHOODS AND BINARY CLASSIFIERS [10] (1) Consider a conditional I.I.D. Bernoulli random variable: YX Be(p) is with parameter p[0,1]. Given n observations yx= y1x1,,ynxn of YX, derive the log likelihood function. [4] (2) Consider a multi-parameter binary classification model: Y^= f(X;), with parameters where YY^Be(Y^) is I.I.D. Given n observations yy^=y1y^1,,yny^n. Derive the log likelihood function. [4] (3) Write down a simple mathematical expression for the learned parameters using the log likelihood function. [2]