We want to build a bayes classifier for a binary classification task (y = 1 or y = 2) with two binary features (x1 and x2). we know the following quantities: (1) p(y = 1) = 0.6; (2) p(x1 = 0, x2 = 0|y = 1) = 0.3, p(x1 = 0, x2 = 1|y = 1) = 0.1, p(x1 = 1, x2 = 0|y = 1) = 0.4, p(x1 = 1, x2 = 1|y = 1) = 0.2, and (3) p(x1 = 0, x2 = 0|y =

3 qrs + 3/2 xy hope this : /

step-by-step explanation:

answer:   expression= p+p*d%

price reduction + sale price = $625

sale price: $p+$p*d%

where d% is the percentage of discount

step-by-step explanation:

original price = p

price went down by $150 price reduction $p*d%

sale price= $ 475

therefore the price before sale is: $625

and the expression that shows the price before sale is: p+p*d%

i have no clue what you just said. write a question in english?