Lorenzo
Authored by Lorenzo Spina
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1st - 5th Grade
Used 5+ times
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26 questions
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1.
MULTIPLE SELECT QUESTION
45 sec • 1 pt
An algorithm iteratively learns how to classify data by maximising the accuracy of its performance. However, what would likely happen when the dataset is highly unbalanced (e.g., 99% of positives and 1% of negatives)?
the algorithm is not able to learn because the accuracy will always stay too low (~0.01)
the algorithm is not able to learn because the accuracy will always stay too high (~0.99)
accuracy is never related to the balancement of the classes
I don't know
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
An algorithm iteratively learns how to classify data by maximising the accuracy of its performance. However, what would likely happen when the dataset is highly unbalanced (e.g., 99% of positives and 1% of negatives)?
the algorithm is not able to learn because the accuracy will always stay too low (~0.01)
the algorithm is not able to learn because the accuracy will always stay too high (~0.99)
accuracy is never related to the balancement of the classes
I don't know
3.
MULTIPLE SELECT QUESTION
45 sec • 1 pt
You are developing a model for sick patient detection (sick=positive, healthy=negative). Which metric would you use?
Accuracy
Precision
Recall
I don't know
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
You are developing a model for sick patient detection (sick=positive, healthy=negative). Which metric would you use?
Accuracy
Precision
Recall
I don't know
5.
MULTIPLE SELECT QUESTION
45 sec • 1 pt
You are developing a model for email spam detection (spam=positive, non-spam=negative). Which metric would you use?
Accuracy
Precision
Recall
I don't know
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
You are developing a model for email spam detection (spam=positive, non-spam=negative). Which metric would you use?
Accuracy
Precision
Recall
I don't know
7.
MULTIPLE SELECT QUESTION
45 sec • 1 pt
You are developing a model for fraudolent transaction detection (fraudolent=positive, non-fraudolent=negative). Which metric would you use?
Accuracy
Precision
Recall
I don't know
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