Answer:
Bias is the difference between the average prediction of our model and the correct value which we are trying to predict and variance is the variability of model prediction for a given data p[oint or a value which tells us the spread of our data the variance perform very well on training data but has high error rates on test data on the other hand if our model has small training sets then it's going to have smaller variance & & high bias and its contribute more to the overall error than bias. If our model is too simple and has very few parameters then it may have high bias and low variable. As the model go this is conceptually trivial and is much simpler than what people commonly envision when they think of modelling but it helps us to clearly illustrate the difference bewteen bias & variance.
10^6 = 1,000,000
10^2 = 100
1,000,000 / 100 = 10,000
so 8.76x10^6 is 10,000 times greater than
165% of what? If you mean 165% of 1, that's 1.65, which is 1 and 13/20
Answer:
SSS
Step-by-step explanation:
Given that the sides are equal and no angles are given
Well here's the equation 4x3 x2=24 for both of the sides and the top 10x2 because if 4 is the bottom and the sides are 6 6-4=2 so 10x2=20 and we add the areas and
<u><em>20</em></u>
<u><em>+</em></u>
<u><em>24</em></u>
_____
44 is the combined areas (Your answer 44)
HOPE THIS HELPS :D
