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:
rationalize my skill capability
Step-by-step explanation:
Answer:
Step-by-step explanation:
If 20-2.3=17.7, then if you add 17.7 to 2.3. it equals 20 which is called the communicative property because whatever you add or subtract, the answer is the same
17.7+2.3=2.3+17.7
The length of the base is 27 and the length of the height is 17.
To find the answer, you need to add up each side twice and set it equal to 88.
x-6+x-6+x+4+x+4=88
That is equal to: 4x - 4 = 88
Add 4 to both sides: 4x = 92
Divide by 4: x = 23
Now plug 23 in for x:
Base: 23 + 4 = 27
Height: 23-6=17
