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Databricks Exam Databricks Certified Professional Data Scientist Topic 4 Question 61 Discussion

Actual exam question for Databricks's Databricks Certified Professional Data Scientist exam

Question #: 61
Topic #: 4

[All Databricks Certified Professional Data Scientist Questions]

You are working in a data analytics company as a data scientist, you have been given a set of various types of Pizzas available across various premium food centers in a country. This data is given as numeric values like Calorie. Size, and Sale per day etc. You need to group all the pizzas with the similar properties, which of the following technique you would be using for that?

AAssociation Rules

BNaive Bayes Classifier

CK-means Clustering

DLinear Regression

EGrouping
Using K means clustering you can create group of objects based on their properties. Where K is number of the groups. In this case, in each group you determine the center of the group and then find the how far each object characteristics from the center. If it is near the center than it can be part of the group. Suppose we have 100 objects and we need to determine 4 groups. Hence, here K=4. Now we determine 4 center values and based on that center value we determine the distance of each object from the center.

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Suggested Answer: C

by Whitney at Jun 03, 2024, 11:21 AM

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Jacinta

1 years ago

I bet the person who came up with 'Grouping' as an answer was just really hungry and wanted to eat all the pizzas.

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Zana

11 months ago

C) K-means Clustering

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Wynell

11 months ago

A) Association Rules

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German

1 years ago

Haha, linear regression? For grouping pizzas? I'd like to see how that's supposed to work. K-means is the obvious answer.

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Lashon

1 years ago

Wait, why would you use a Naive Bayes classifier for this? That's more for classification, not grouping. K-means is the clear choice.

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Mattie

12 months ago

Using K-means Clustering, we can determine groups of pizzas with similar characteristics.

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Desiree

12 months ago

K-means Clustering is the best technique for grouping similar objects based on their properties.

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Lavonda

1 years ago

Naive Bayes Classifier is used for classification, not grouping.

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Cristy

1 years ago

I would go with Naive Bayes Classifier, it might work well too.

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Stevie

1 years ago

I agree with you, K-means Clustering is a good choice for this task.

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Carolann

1 years ago

I think I would use K-means Clustering for grouping the pizzas.

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Kizzy

1 years ago

K-means clustering is definitely the way to go here. Grouping similar pizzas based on their properties is exactly what the question is asking for.

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Stacey

12 months ago

Definitely, K-means clustering is the most suitable method for grouping pizzas with similar properties in this scenario.

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Burma

12 months ago

Yes, K-means clustering is perfect for this task. It helps in creating distinct groups based on similarities.

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Tanesha

1 years ago

I agree, K-means clustering is the best technique for grouping similar pizzas based on their properties.

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