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.
Answer:
<u><em>-71</em></u>
Step-by-step explanation:
15 liters of Yoda Soda for the 36 guests.
Answer:
j=8
Step-by-step explanation:
30-6=24 divived by 3 = 8 which means jordans age is 8 and matthew is 16
Answer:
3
Step-by-step explanation:
Given
15 gold ribbons
22 blue ribbons
53 red ribbons
Total of 53 + 22 + 15 = 90 ribbons
Total number of students = 12 boys + 18 girls = 30 students.
If evenly divided, each student will have 90/30 = 3 ribbons
The expression to solve would basically be the amalgamation of what we did above:
(53 + 22 + 15)/(12+18)
