CertNexus Exam AIP-210 Topic 1 Question 32 Discussion

Actual exam question for CertNexus's AIP-210 exam

Question #: 32
Topic #: 1

The following confusion matrix is produced when a classifier is used to predict labels on a test dataset. How precise is the classifier?

A48/(48+37)

B37/(37+8)

C37/(37+7)

D(48+37)/100

Show Suggested Answer

Suggested Answer: D

Stratification is not a valid cross-validation method, but a technique to ensure that each subset of data has the same proportion of classes or labels as the original data. Stratification can be used in conjunction with cross-validation methods such as k-fold or leave-one-out to preserve the class distribution and reduce bias or variance in the validation results. Bootstrapping, k-fold, and leave-one-out are all valid cross-validation methods that use different ways of splitting and resampling the data to estimate the performance of a machine learning model.

by Andra at Sep 17, 2024, 05:26 AM

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Lavera

Hmm, I wonder if the test maker has a sense of humor. Maybe they'll throw in a 'banana' option just to see who's paying attention!

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Karol

3 days ago

I'm confident the answer is A. This is a straightforward calculation of precision, and the other options don't make sense given the information provided.

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Una

5 days ago

I see your point, but I still think option A is the right choice because it considers both true positives and false positives.

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Rashida

6 days ago

I disagree, I believe the correct calculation is in option B.

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Una

7 days ago

I think the precision of the classifier is calculated by option A.

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Tu

8 days ago

But option A considers true positives and false positives, which are important for precision.

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Gilma

10 days ago

The correct answer is A) 48/(48+37), which represents the precision of the classifier. The confusion matrix shows the true positive and false positive counts, and precision is the ratio of true positives to the sum of true positives and false positives.

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Chauncey

10 days ago

I disagree, I believe the correct calculation is in option B.

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Tu

25 days ago

I think the precision of the classifier is calculated by option A.

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