QUIZ BAn 210
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Seneca College *
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Course
21O
Subject
Electrical Engineering
Date
Apr 3, 2024
Type
docx
Pages
7
Uploaded by LieutenantCloverBison35
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Question 2
Selected Answer:
Answers:
The following is true.
In neural net modelling, users can input di erent optimization techniques
Overfitting is more of a problem with regression techniques than neural net techniques
In neural net modelling, users can input different optimization techniques
traditional models work better than neural net models in image applications
all of the above
none of the above
Question 3
Selected Answer:
Answers:
The following is true
Drop o rates help models to generalize well
Drop off rates help models to generalize well
bias and variance are only real issues with AI or neuural net models
correlation output is a form of machine learning
all of the above
none of the above
Question 4
Selected Answer:
Answers:
The following is true
all of the above
least squares is used primarily in AI.
out of 1 points
1
1 out of 1 points
out of 1 points
0
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least squares is used in cluster segmentation
least squares is used in factor analysis
all of the above
none of the above
Question 5
Selected Answer:
Answers:
Least squares is the concept in attempting to minimize randomness in a model
true
true
false
Question 6
Selected Answer:
Answers:
The following is true
stepwise regression is a model variable selection technique
stepwise regression is a model variable selection technique
factor analysis in theory can be used as a model variable selection technique
EDA's can be used to create new variables
all of the above
none of the above
Question 7
The following is true
1 out of 1 points
0 out of 1 points
0 out of 1 points
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3/28/23, 11:45 PM
Review Test Submission: rb1paquiz5_mar27 – Predictive ...
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Selected Answer:
Answers:
random forests generate model scores
neural nets require only 2 datasets
regression models require only 2 datasets
random forests generate model scores
all of the above
none of the above
Question 8
Selected
Answer:
Answers:
The following is true
R2 could be used to explain a logistic model output
R2 could be used to explain a logistic model output
confusion matrix could be used to evaluate the performance of a multiple regression model predicting
income
accuracy rates are the most important performance metric in consumer behaviour predictive models
all of the above
none of the above
Question 9
Selected Answer:
Answers:
The following is true
all of the above
stepwise regression is a form of machine learning
factor analysis is a form of machine learning
1 out of 1 points
0 out of 1 points
3/28/23, 11:45 PM
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exploratory data analysis is a form of machine learning
all of the above
none of the above
Question 10
Selected Answer:
Answers:
Neural net modelling or AI modelling is completely dependant on the machine and algorithm.
false
true
false
Question 11
Selected Answer:
Answers:
In selecting model variables using stepwise regression
b and c
the practitioner can use p-values as one option
the practitioner can use drop-off rates as one option
the practitioneer can use forward stepwise regression as one option
b and c
a and c
Question 12
Selected Answer:
The following is true
backward stepwise is another stepwise regression option
1 out of 1 points
0 out of 1 points
1 out of 1 points
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Answers:
backward stepwise is another stepwise regression option
The least squares value in a perfect regression model would be 1.
random forests are built on a development sample and then validated against a validation dataset
all of the above
none of the above
Question 13
Selected Answer:
Answers:
The following is true
gradient boosting is another form of decision-tree modelling
In developing models,modelling techniques are applied right after the creation of the analytical file
gradient boosting is another form of decision-tree modelling
Selection of the modelling technique is the most important element in building models
all of the above
none of the above
Question 14
Selected Answer:
Answers:
The following is true
all of the above
modelling weights or coefficients are determined by its impact on the target variable
modelling weights or coefficients are determined by multicollineaarity.
modelling weights or coefficients are determined by the scale or magnitude of the given variable
all of the above
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Tuesday, March 28, 2023 11:44:39 PM EDT
none of the above
Question 15
Selected Answer:
Answers:
Multicollinearity is a serious problem when a model variable has a di erent trend than observed in correlation
false
true
false
←
OK
0 out of 1 points
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