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Amazon Exam AIF-C01 Topic 5 Question 16 Discussion

Actual exam question for Amazon's AIF-C01 exam
Question #: 16
Topic #: 5
[All AIF-C01 Questions]

A company wants to classify human genes into 20 categories based on gene characteristics. The company needs an ML algorithm to document how the inner mechanism of the model affects the output.

Which ML algorithm meets these requirements?

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Suggested Answer: A

by Stevie at Dec 09, 2024, 05:13 AM

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Abel
2 months ago
Linear regression might not be the best fit for this, as it is more suited for predicting continuous values.
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Roxanne
2 months ago
I see both points, but I think Logistic regression could also be a good choice.
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Louis
2 months ago
I disagree, I believe Neural networks would be more suitable for this task.
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Mariann
2 months ago
I think Decision trees would be the best option for this.
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Man
2 months ago
Linear regression? Seriously? This is like trying to fit a square peg into a round hole. Neural networks are the only choice here.
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Miesha
3 months ago
Logistic regression? Nah, that's for simple binary classification. This problem calls for the big guns - neural networks!
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Emile
2 months ago
Logistic regression is not suitable for this problem, neural networks offer more flexibility.
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Laquanda
2 months ago
Linear regression is too simplistic for this kind of gene classification.
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Burma
2 months ago
I agree, decision trees might not be able to capture the intricate relationships in the data.
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Sheridan
2 months ago
Neural networks are definitely the way to go for this complex task.
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Audria
3 months ago
Decision trees? Sounds like a lumberjack solution to a genetic problem. Neural networks are the real deal.
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Launa
3 months ago
Neural networks are the way to go! They can handle the complexity of gene characteristics like a boss.
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Quentin
1 months ago
Linear regression and logistic regression are more suited for continuous data, not gene classification.
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Georgeanna
1 months ago
Decision trees might not be able to capture all the nuances of gene characteristics.
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Colette
1 months ago
I agree, they can handle the complexity of gene characteristics really well.
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Antione
2 months ago
Neural networks are definitely the best choice for classifying human genes.
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