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Databricks Exam Databricks-Certified-Professional-Data-Scientist Topic 4 Question 68 Discussion

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

Question #: 68
Topic #: 4

[All Databricks Certified Professional Data Scientist Exam 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 Harrison at Sep 09, 2024, 07:57 AM

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Harley

11 days ago

I believe Linear Regression could also be used to group the pizzas effectively.

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Evelynn

11 days ago

Haha, Naive Bayes for pizza clustering? What is this, a pizza-flavored machine learning algorithm? K-means all the way!

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Marlon

12 days ago

I would go with Association Rules to group the pizzas based on their properties.

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Annmarie

18 days ago

Yup, K-means is the way to go. Although I do wonder how they'll decide on the number of groups. Guess we'll have to see!

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Kanisha

19 days ago

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

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Kaitlyn

22 days ago

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

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Bobbye

23 days ago

Pfft, linear regression for pizza grouping? What is this, amateur hour? K-means all the way, baby!

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Davida

25 days ago

I agree, K-means is definitely the right choice here. Gotta love that sweet, sweet clustering power!

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Eva

2 days ago

It's all about finding those center values and determining the distance from them.

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Margot

3 days ago

Definitely, K-means clustering will help us group the pizzas based on their properties.

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Elenor

12 days ago

K-means Clustering is the way to go for grouping those pizzas.

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Lachelle

27 days ago

K-means clustering sounds like the way to go for this problem. Grouping the pizzas based on their properties makes a lot of sense.

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Lajuana

19 days ago

Yes, K-means clustering is a great way to categorize the pizzas with similar characteristics.

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Isidra

21 days ago

I agree, K-means clustering would be the best technique to group the pizzas based on their properties.

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