Given the dataset shown below, we want to predict whether a baby finds a particular type of food Appealing or not based on the food's Temperature, Taste, and Size.

$($Hint: $I(P(c_1),$dots,$P(c_2))=-{\displaystyle \underset{i=1}{\overset{k}{}}}P(c_i)lo{g}_2(P(c_i)))$

$\backslash$table$[[$Temperature$,$Taste,Size,Appealing$],[$Hot$,$Salty,Small,No$],[$Cold$,$Sweet,Large,No$],[$Cold$,$Sweet,Large,No$],[$Cold$,$Sour,Small,Yes$],[$Hot$,$Sour,Small,Yes$],[$Hot$,$Salty,Large,No$],[$Hot$,$Sour,Large,Yes$],[$Cold$,$Sweet,Small,Yes$],[$Cold$,$Sweet,Small,Yes$],[$Hot$,$Salty,Large,No$]]$b$)(08pts)$ Assume that Taste is chosen for the root of the decision tree. What is the information gain associated with this attribute?