AI Midterm Lab Quiz 2_ Attempt review
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AMA Computer University *
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Course
2333T
Subject
Computer Science
Date
Jun 9, 2024
Type
Pages
6
Uploaded by GrandGalaxyApe34
Started on
Saturday, 8 June 2024, 7:02 AM
State
Finished
Completed on
Saturday, 8 June 2024, 7:20 AM
Time taken
17 mins 29 secs
Marks
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Grade
80.00
out of 100.00
Question 1
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Question 2
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Question 3
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What is the "M" step in the EM algorithm?
a.
The step where the expectation of the latent variables is calculated
b.
The step where the prediction accuracy of the model is calculated
c.
The step where the model parameters are updated
✓
d.
The step where the likelihood of the model is maximized
What is the main advantage of the Hebb rule?
a.
It is fast to converge
✓
b.
It is able to handle nonlinear relationships
c.
It is easy to implement
d.
It is able to handle large datasets
What is the Hebb rule?
a.
A rule used to calculate the output of a neural network
b.
A rule used to adjust the weights in a neural network
✓
c.
A rule used to determine the structure of a neural network
d.
A rule used to determine the input to a neural network
08/06/2024, 10:20
Midterm Lab Quiz 2: Attempt review
https://trimestral.amaesonline.com/2333/mod/quiz/review.php?attempt=117976&cmid=64470
1/6
Question 4
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Question 5
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Question 6
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Question 7
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What is the EM algorithm used to estimate in the "E" step?
a.
The prediction accuracy of the model
b.
The latent variables
✓
c.
The model parameters
d.
The likelihood of the model
What is the Naive Bayes classifier used for?
a.
To predict the value of a continuous variable
b.
To classify data into different categories based on certain features
✓
c.
To predict the probability of an event occurring
d.
All of the above
What is the equation for the Hebb rule?
a.
w(new) = w(old) + η(output - target)x(input)
b.
w(new) = w(old) + η(target - output)x(input)
c.
w(new) = w(old) + η(input - output)x(target)
d.
w(new) = w(old) + η(output)x(input)
✓
What is the advantage of using the Gaussian Naive Bayes classifier over other types of Naive Bayes classifiers?
a.
It is more accurate
b.
It is able to handle categorical features
×
c.
It is able to handle continuous features
d.
It is faster to train and predict
08/06/2024, 10:20
Midterm Lab Quiz 2: Attempt review
https://trimestral.amaesonline.com/2333/mod/quiz/review.php?attempt=117976&cmid=64470
2/6
Question 8
Correct
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Question 9
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Question 10
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Question 11
Correct
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What is the advantage of the Naive Bayes classifier over other classifiers?
a.
It is faster to train and predict
✓
b.
It is more flexible
c.
It is more accurate
d.
It is able to handle large amounts of data
What is the EM algorithm used to optimize in the "M" step?
a.
The likelihood of the model
✓
b.
The prediction accuracy of the model
c.
The model parameters
d.
The latent variables
What is the disadvantage of the Naive Bayes classifier?
a.
It is slower to train and predict
b.
It is less accurate
c.
It is inflexible
d.
It is unable to handle large amounts of data
×
What is the learning rule for a perceptron called?
a.
The Hebbian Rule
✓
b.
The Perceptron Learning Algorithm
c.
The Backpropagation Algorithm
d.
The Delta Rule
08/06/2024, 10:20
Midterm Lab Quiz 2: Attempt review
https://trimestral.amaesonline.com/2333/mod/quiz/review.php?attempt=117976&cmid=64470
3/6
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