Step-by-step explanation:
To check out how efficient or accurate a model is, we use the akaike information criterion or the Bayesian. If the AIC or BIC are lower, then this model would be better. They are also used to control for model complexity
Akaike information criterion = 2k-2ln where k is the number of parameter. A higher k gives a higher AIC.
In the real world complex models are discouraged and avoided since
1. They cause data to be over fitted and can capture noise and information from this data.
2. They are complex and therefore difficult to interpret
3. They consume a lot of time and computing them has several inefficiencies.
Using these two as measure of performance, we can select optimal choice of independent variable.
With forward/backward regression, we are able to put new variables in the model or remove from it. The best is the one with lowest AIC.
Answer:
P = 16j+4h
Step-by-step explanation:
To find the perimeter, we add up all the sides.
There are 6 sides in this figure
4 sides have the length of 4j (they are the same length because of the single line)
2 sides have the length of 2h (they are the same length because of the double line)
P = 4(4j) + 2( 2h)
P = 16j+4h
Answer:
(x-1)(x-2)(x-3)
Step-by-step explanation:
hy vọng nó giúp
Answer:
9 is the answer, wanna know how?
Step by Step explanation : So you do this and that equals 9.
Answer:
32.5.
Step-by-step explanation:
32 + 20 + 40 + 44 + 21 + 38 = 52 + 84 + 59 = 195
There are 6 terms in the data set.
195 / 6 = 65 / 2 = 32.5.
Hope this helps!
