Suppose that we apply bagging and random forests respectively to Weekly data set (the same one used in the assignment) and obtain two models M1 and M2. Given the codes as below, which model is from bagging and which one is from random forests? In general, which model (M1 or M2) is more likely to have a higher prediction accuracy on the new testing data set? M1 <- randomForest (Direction M2 <- random Forest (Direction ., data = Weekly, mtry - 2) ., data = Weekly, mtry = 6)

i dont know sorry

step-by-step explanation:

if the pizza is divided equally into 2 equal halves then you would get

πr^2/2

where r is the radius of the pizza.

happy to

pls mark as brainliest

step-by-step explanation:

ok one would be money, and the other would be refreshments or something similar. if each bag of popcorn is 5.00 and each drink is half of that that means drinks are 2.50 the proper way to do that would to look and see how much of each you can buy without exceeding a limit of 30.00