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Databricks Certified Professional Data Scientist Exam - Topic 5 Question 55 Discussion

Actual exam question for Databricks's Databricks Certified Professional Data Scientist exam
Question #: 55
Topic #: 5
[All Databricks Certified Professional Data Scientist Questions]

Your company has organized an online campaign for feedback on product quality and you have all the responses for the product reviews, in the response form people have check box as well as text field. Now you know that people who do not fill in or write non-dictionary word in the text field are not considered valid feedback. People who fill in text field with proper English words are considered valid response. Which of the following method you should not use to identify whether the response is valid or not?

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Suggested Answer: B

by Helaine at Mar 17, 2024, 10:14 AM

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Dick
4 months ago
All of them can be used, so D seems right.
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Mignon
5 months ago
Surprised that any of these methods could work!
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Clorinda
5 months ago
Random Decision Forests? Really?
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Nieves
5 months ago
I think Logistic Regression is better for this.
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Dwight
5 months ago
Naive Bayes is great for text classification!
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Lucille
6 months ago
I’m a bit confused about the "Any one of the above" option. I thought all methods could be applied, but maybe one is just not as effective?
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Nathan
6 months ago
I practiced a similar question where we had to choose the right model for binary classification, and I feel like any of these methods could work, but I’m leaning towards Random Decision Forests being less suitable.
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Aron
6 months ago
I think Logistic Regression might not capture the complexity of the text data as well as the others, but I need to double-check that.
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Wade
6 months ago
I remember we discussed how Naive Bayes is good for text classification, but I'm not sure if it's the best choice here.
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Jacki
6 months ago
I think the key here is to focus on preprocessing the text data properly. We'll need to handle things like stop words, stemming/lemmatization, and maybe even sentiment analysis to identify the "non-dictionary words" mentioned in the prompt.
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Nu
6 months ago
Hmm, I'm not sure Naive Bayes is the best choice here. Since we're dealing with text data, a model like Random Forests or Support Vector Machines might be more appropriate.
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Josefa
6 months ago
I'm a bit confused on the best approach here. Should we be using a supervised learning algorithm since we have labeled data, or would an unsupervised method like clustering work better?
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Allene
6 months ago
This seems like a straightforward text classification problem. I'd probably start with a simple logistic regression model and see how that performs.
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Mari
6 months ago
I'm a little confused by the wording of the question. Is the relational algebra expression supposed to be provided, or is the goal to just match the SQL statements to the correct operation? I'll need to clarify that before I can confidently answer.
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Lazaro
6 months ago
I'm pretty confident that Express Indexing is the right answer. It's designed to optimize performance by reducing the overhead of indexing data.
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Alita
6 months ago
Okay, I've got this. The correct answer is option C - the training loss decreases while the validation loss increases. That means the model is performing well on the training data but not generalizing well to the validation data, which is a clear sign of overfitting.
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Jina
11 months ago
I'd go with the 'Magic 8-Ball' method. Shake it, and whatever answer it gives, that's the one we use!
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Genevive
9 months ago
User4: Yeah, those methods sound more appropriate for identifying valid responses.
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Dottie
9 months ago
User3: I think we should consider using Naive Bayes or Logistic Regression for this.
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Ramonita
10 months ago
User2: I agree, we need a more reliable method to determine valid feedback.
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Doug
10 months ago
User1: That's a funny suggestion, but I don't think we can use the 'Magic 8-Ball' method for this.
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Lilli
11 months ago
Wait, are we sure we can't just use a good old-fashioned dictionary lookup? That seems like the easiest solution to me.
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Lonny
11 months ago
Random Decision Forests? Nah, that's overkill. We don't need that much complexity for something this straightforward.
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Delmy
11 months ago
Logistic Regression sounds like a solid choice too. It's a classic for this kind of task.
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Lilli
10 months ago
I'm not sure about Naive Bayes, it might not be the best method for this particular problem.
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Sabrina
10 months ago
I think Random Decision Forests could also be a good option for identifying valid responses.
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Jose
10 months ago
I agree, Logistic Regression is a classic choice for this type of problem.
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Jamal
11 months ago
I think Naive Bayes would be the way to go here. It's great for binary classification problems like this one.
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Yun
10 months ago
User 3: Random Decision Forests might be a good option too, don't you think?
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Merilyn
11 months ago
User 2: I think Logistic Regression could also work well in this scenario.
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Carissa
11 months ago
User 1: I agree, Naive Bayes is perfect for this kind of problem.
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Leonora
12 months ago
But Naive Bayes may not perform well with high-dimensional independent variables like in this case.
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Luisa
12 months ago
I disagree, I believe Naive Bayes can be effective in this scenario.
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Leonora
1 year ago
I think we should not use Naive Bayes to identify valid responses.
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