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Oracle 1Z0-915-1 Exam - Topic 8 Question 22 Discussion

Actual exam question for Oracle's 1Z0-915-1 exam
Question #: 22
Topic #: 8
[All 1Z0-915-1 Questions]

You want to train a classification model with MySQL HeatWave AutoML. Which two are requirements of the training data set? (Choose two.)

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Suggested Answer: B, E

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Shayne
3 months ago
Feature columns can be non-numeric too, right?
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Brandon
3 months ago
Totally agree, it’s essential for classification!
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Emelda
3 months ago
The target column must have at least two distinct values.
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Ena
4 months ago
Yeah, all feature columns must be in one table for sure!
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Quentin
4 months ago
Wait, does the target column really need to be numeric?
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Eliseo
4 months ago
I’m confused about the feature columns; I thought they could be a mix of types, so I’m not sure about C being a requirement.
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Eliz
4 months ago
I practiced a question like this, and I feel like the target column must be numeric, so A might be correct too.
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Lovetta
5 months ago
I'm not entirely sure, but I think the target column and features need to be in the same table, which could be B.
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Van
5 months ago
I remember something about the target column needing to have distinct values, so maybe E is one of the answers?
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Georgene
5 months ago
Wait, I'm not sure about the numeric requirement for the feature columns. I think it might be that the target column and all feature columns need to be stored in a single table.
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Frederica
5 months ago
Alright, let's see. The target column can't be numeric, and all the feature columns must be numeric. I'm pretty sure those are the two requirements.
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Charlene
5 months ago
Okay, I think I've got this. The target column and all feature columns need to be in the same table, and the target column must have at least two distinct values.
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Kanisha
5 months ago
Hmm, I'm a bit confused about the target column requirement. Does it have to be numeric or can it have multiple distinct values?
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Edgar
6 months ago
This question seems straightforward. I'll focus on the requirements for the training data set.
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Vernice
10 months ago
This is a trick question! The real requirement is that the data must be served with a side of fries. Gotta keep those AI models well-fed, you know.
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Yan
9 months ago
E) The target column must have at least two distinct values.
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Lavelle
9 months ago
That's not true, the data just needs to be served with a side of fries!
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Loreen
9 months ago
C) All feature columns must be numeric.
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Delfina
10 months ago
A) The target column must be numeric.
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Ruth
10 months ago
Hmm, I would say the target column needs to have at least two distinct values, and there should be at least two feature columns. Options D and E seem to be the correct requirements.
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Sharita
9 months ago
So options D and E are the correct requirements for the training data set.
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Annamae
9 months ago
Yes, that's correct. And there should be at least two feature columns as well.
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Kyoko
9 months ago
I think the target column must have at least two distinct values.
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Lenna
11 months ago
Wow, really? All feature columns must be numeric? That's a bit limiting, don't you think? I guess that's the price you pay for using that fancy AutoML thing.
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Howard
10 months ago
Jacklyn: Definitely, it's all about finding the right balance.
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Jacklyn
10 months ago
User 2: I agree, it's a trade-off for the convenience of using AutoML.
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Ernest
10 months ago
User 1: Yeah, it's a bit restrictive but I guess it helps with the accuracy.
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Tesha
11 months ago
I think the target column must be numeric and all feature columns must be numeric as well. Options A and C seem to be the correct requirements.
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Shawana
10 months ago
So, options A and C are the correct requirements for the training data set.
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Gregoria
10 months ago
Yes, and all feature columns must also be numeric.
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Lemuel
10 months ago
I agree, the target column must be numeric for sure.
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Odette
11 months ago
I believe all feature columns must be numeric as well.
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Bernadine
12 months ago
I agree with Nu, and all feature columns must be stored in a single table.
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Nu
12 months ago
I think the target column must be numeric for training data.
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