ISYE 6501 QUIZ 2 UPDATED ACTUAL EXAM QUESTIONS
AND CORRECT ANSWERS
Question 1.
If you have less data than features, what is likely to occur?
ANSWER
Overfitting
Question 2.
What can too many factors lead to?
ANSWER
Fitting random effects
Question 3.
Reducing variables will result in
ANSWER
Simple Models
Question 4.
Things that cannot be used due to legal requirements
ANSWER
Forbidden Factors
Question 5.
Gathering more data to develop a better model
ANSWER
Exploration
,Question 6.
Using data sooner to get less accurate, but more immediate results
ANSWER
Exploitation
Question 7.
Forward selection starts with what
ANSWER
No factors
Question 8.
How do you find the best factor in forward selection?
ANSWER
look for p <= 0.15 or p <= 0.1
Question 9.
What does a low p value mean
ANSWER
Coefficient is not 0
Question 10.
What is the null hypothesis in a feature test
ANSWER
Coefficient is 0
Question 11.
Backwards feature selection starts with
ANSWER
All factors
, Question 12.
What is a benefit of classical feature selection
ANSWER
Scaling is not required
Question 13.
A combination of forward and backward feature selection
ANSWER
Stepwise regression
Question 14.
Does the best thing without taking into consideration any future events
ANSWER
Greedy Algorithm
Question 15.
Stepwise, Backward and Forward feature selection are what kind of approach
ANSWER
Greedy
Question 16.
Lasso, ElasticNet and Ridge are examples of what kind of approach
ANSWER
Global
Question 17.
The tau value in lasso make sure what doesn't get large
ANSWER
Sum of the absolute value of the coefficients
AND CORRECT ANSWERS
Question 1.
If you have less data than features, what is likely to occur?
ANSWER
Overfitting
Question 2.
What can too many factors lead to?
ANSWER
Fitting random effects
Question 3.
Reducing variables will result in
ANSWER
Simple Models
Question 4.
Things that cannot be used due to legal requirements
ANSWER
Forbidden Factors
Question 5.
Gathering more data to develop a better model
ANSWER
Exploration
,Question 6.
Using data sooner to get less accurate, but more immediate results
ANSWER
Exploitation
Question 7.
Forward selection starts with what
ANSWER
No factors
Question 8.
How do you find the best factor in forward selection?
ANSWER
look for p <= 0.15 or p <= 0.1
Question 9.
What does a low p value mean
ANSWER
Coefficient is not 0
Question 10.
What is the null hypothesis in a feature test
ANSWER
Coefficient is 0
Question 11.
Backwards feature selection starts with
ANSWER
All factors
, Question 12.
What is a benefit of classical feature selection
ANSWER
Scaling is not required
Question 13.
A combination of forward and backward feature selection
ANSWER
Stepwise regression
Question 14.
Does the best thing without taking into consideration any future events
ANSWER
Greedy Algorithm
Question 15.
Stepwise, Backward and Forward feature selection are what kind of approach
ANSWER
Greedy
Question 16.
Lasso, ElasticNet and Ridge are examples of what kind of approach
ANSWER
Global
Question 17.
The tau value in lasso make sure what doesn't get large
ANSWER
Sum of the absolute value of the coefficients
