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CompTIA DY0-001 Exam - Topic 4 Question 8 Discussion

Actual exam question for CompTIA's DY0-001 exam

Question #: 8
Topic #: 4

[All DY0-001 Questions]

The term "greedy algorithms" refers to machine-learning algorithms that:

Aupdate priors as more data is seen.

Bexamine even/ node of a tree before making a decision.

Capply a theoretical model to the distribution of the data.

Dmake the locally optimal decision.

Show Suggested Answer

Suggested Answer: D

Greedy algorithms build the solution iteratively by choosing at each step the option that appears best at that moment, without reconsidering earlier choices.

by Rusty at Jul 14, 2025, 12:25 AM

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Roxanne

9 months ago

I thought they examined every node before deciding?

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Rene

9 months ago

Totally agree, it's all about local optimization.

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Shaunna

9 months ago

They don't update priors, that's a different thing!

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Alishia

10 months ago

Wait, isn't that a bit simplistic for complex problems?

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Silva

10 months ago

Greedy algorithms make the locally optimal decision!

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Kristel

10 months ago

I’m a bit confused; I thought greedy algorithms were more about examining nodes in trees. Could it be B?

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Lonny

10 months ago

I feel like I’ve seen a question similar to this before, and it was definitely about local decisions. D seems right to me.

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Sherman

11 months ago

I remember something about updating priors, but I’m not sure if that’s what greedy algorithms do. Maybe it’s A?

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Michal

11 months ago

I think greedy algorithms are about making the best local choice at each step, so I’m leaning towards option D.

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Elvis

11 months ago

I'm a little uncertain about this one. The options seem to be describing different aspects of machine learning algorithms, but I'm not sure which one specifically applies to "greedy algorithms." I'll have to review my notes and see if I can figure this out.

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Heike

11 months ago

Okay, I've got this. Greedy algorithms are all about making the best decision at each step, even if it's not the absolute best overall solution. That sounds like option D to me - making the locally optimal decision. I'm confident that's the right answer.

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Vincenza

11 months ago

Hmm, I'm a bit confused on this one. I know greedy algorithms are used in machine learning, but I'm not sure exactly how they work. I'll have to think this through carefully.

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Lorita

11 months ago

I'm pretty sure this is asking about greedy algorithms, which are a type of optimization algorithm that makes the locally optimal choice at each stage with the hope of finding a global optimum. I think the answer is D.

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Boris

1 year ago

Exactly, it's all about immediate gratification in terms of decision-making.

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Dick

1 year ago

I feel like C is the way to go here. Applying a theoretical model to the data distribution seems like a pretty 'greedy' thing to do, don't you think? Gotta love those machine learning algorithms!

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Alesia

1 year ago

Haha, greedy algorithms, eh? Sounds like my friends when we go out for dinner - they just want the biggest plate and don't care about sharing! But in all seriousness, I'm going with D on this one.

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Oneida

12 months ago

I agree, D does sound like the best option for greedy algorithms.

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Bernardine

1 year ago

So, it's about choosing the option that seems best at the moment without considering the future consequences?

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Joanne

1 year ago

Hmm, I'm not so sure. I was thinking it might be B, since greedy algorithms often explore the entire decision tree before making a move. But D makes sense too. Decisions, decisions...

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Elvera

1 year ago

I agree with Boris, greedy algorithms aim to make the best choice at each step.

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Ahmed

1 year ago

D. This one seems obvious to me - greedy algorithms always go for the locally optimal decision, without considering the bigger picture. That's kinda their whole thing, right?

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Boris

1 year ago

I think it means making the locally optimal decision.

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Bernardine

1 year ago

What do you think the term 'greedy algorithms' refers to?

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