Answer:
This question doesn't have a solution
Step-by-step explanation:
Step-by-step explanation:
First, note that a flexible statistical learning method refers to using models that take into account agree difference in the observed data set, and are thus adjustable. While the inflexible method usually involves a model that has no regard to the kind of data set.
a) The sample size n is extremely large, and the number of predictors p is small. (BETTER)
In this case since the sample size is extremely large a flexible model is a best fit.
b) The number of predictors p is extremely large, and the number of observations n is small. (WORSE)
In such case overfiting the data is more likely because of of the small observations.
c) The relationship between the predictors and response is highly non-linear. (BETTER)
The flexible method would be a better fit.
d) The variance of the error terms, i.e. σ2=Var(ϵ), is extremely high. (WORSE)
In such case, using a flexible model is a best fit for the error terms because it can be adjusted.
Answer:
100 red bricks
Step-by-step explanation:
Let's say red bricks is equal to 5x
Gray bricks is equal to 2x
We have an equation
2x + 5x = 140
= 7x = 140
Divide through by 7 to get the value of x
X = 140/7
X = 20
Red bricks = 5(x)
= 5(20)
= 100
Gray bricks = 2(x)
= 2(20)
= 40
Therefore in conclusion the number of red bricks is 100.
Answer:
23 degrees
Step-by-step explanation:
6x + 42 = 180
x = 23
Answer:
B
Step-by-step explanation:
Because 9 = 5 +4