Consider a single Boolean random variable Y (the “classification”). Let the prior probability P(Y = true) be π. Let’s try to find π, given a training set D = (y₁, . . . , y_N ) with N independent samples of Y . Furthermore, suppose p of the N are positive and n of the N are negative.

By differentiating the log likelihood L, find the value of π that maximizes the likelihood.

Answer rating: 100% (QA)

Calculation Let the class be Y true The main effect is the classification of a sample The classimputation is the mean value of an Nclass distribution which we assume to be pY 1 05 and nY 1 025 The err... View the full answer