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Dell EMC Exam D-ISM-FN-23 Topic 4 Question 25 Discussion

Actual exam question for Dell EMC's D-ISM-FN-23 exam
Question #: 25
Topic #: 4
[All D-ISM-FN-23 Questions]

What kind of ML explicitly requires splitting the data into training and testing datasets before running an algorithm against that data?

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Suggested Answer: B

by Detra at Feb 07, 2025, 10:39 AM

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Linsey
4 months ago
Splitting the data, the true test of a Supervised Learning model. D) Supervised Learning is the answer, no doubt about it.
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Fabiola
2 months ago
Unsupervised Learning is more about finding patterns in data without labeled examples.
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Sabine
2 months ago
Deep Learning doesn't necessarily require splitting the data like Supervised Learning does.
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My
2 months ago
That's right, you need labeled data to train the model in Supervised Learning.
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Chaya
3 months ago
I agree, Supervised Learning is all about splitting the data for training and testing.
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Venita
4 months ago
D) Supervised Learning, the only way to go. Splitting the data is like cutting the cake - you gotta have a piece for testing, and a piece for training.
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Zana
3 months ago
D) Supervised Learning, the only way to go. Splitting the data is like cutting the cake - you gotta have a piece for testing, and a piece for training.
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Clay
3 months ago
A) Deep Learning
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Dahlia
4 months ago
D) Supervised Learning, of course! Splitting the data is like separating the wheat from the chaff. Can't do Supervised Learning without it.
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Gene
4 months ago
Ah, I was stuck between B) Unsupervised Learning and D) Supervised Learning. Splitting the data is crucial for Supervised Learning, makes sense now.
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Maryann
2 months ago
It's important to remember the distinction between the two types of ML algorithms.
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Graciela
2 months ago
I was also considering B) Unsupervised Learning, but now it's clear.
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Teri
2 months ago
Yes, you're right. Supervised Learning requires splitting the data into training and testing datasets.
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Lazaro
2 months ago
I think the answer is D) Supervised Learning.
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Alisha
4 months ago
I'm not sure, but I think it's D) Supervised Learning too.
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Mireya
4 months ago
D) Supervised Learning is the correct answer. You need to split the data into training and testing sets to properly evaluate the model's performance.
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Virgilio
4 months ago
I agree with Refugia, because supervised learning requires labeled data for training and testing.
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Refugia
4 months ago
I think the answer is D) Supervised Learning.
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