BlackFriday 2024! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions
Mail Us support@pass4success.com
Location US
Mob_nav_barsMENU

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

Actual exam question for Databricks's Databricks-Certified-Professional-Data-Scientist exam
Question #: 68
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?

Show Suggested Answer Hide Answer
Suggested Answer: C

by Harrison at Sep 09, 2024, 07:57 AM

Limited Time Offer

25%

Off

Get Premium Databricks-Certified-Professional-Data-Scientist Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

Submit Cancel
Harley
1 months ago
I believe Linear Regression could also be used to group the pizzas effectively.
upvoted 0 times
...
Evelynn
1 months ago
Haha, Naive Bayes for pizza clustering? What is this, a pizza-flavored machine learning algorithm? K-means all the way!
upvoted 0 times
Leanora
4 days ago
Linear Regression wouldn't be suitable for grouping pizzas, K-means clustering is much more appropriate.
upvoted 0 times
...
Lindsey
7 days ago
Yes, K-means clustering is a great technique for grouping similar objects based on their properties.
upvoted 0 times
...
Colene
26 days ago
Haha, Naive Bayes for pizza clustering? That's a funny thought!
upvoted 0 times
...
Louvenia
27 days ago
K-means clustering is definitely the way to go for grouping pizzas based on their properties.
upvoted 0 times
...
...
Marlon
1 months ago
I would go with Association Rules to group the pizzas based on their properties.
upvoted 0 times
...
Annmarie
2 months 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!
upvoted 0 times
Wilford
13 days ago
Once we have the groups, we can analyze the data and draw insights from it.
upvoted 0 times
...
Brinda
14 days ago
In this case, we can determine the number of groups by setting the value of K.
upvoted 0 times
...
Belen
17 days ago
K-means clustering is a great technique for grouping similar objects based on their properties.
upvoted 0 times
...
...
Kanisha
2 months ago
I agree with Kaitlyn, K-means Clustering is a good choice for this task.
upvoted 0 times
...
Kaitlyn
2 months ago
I think I would use K-means Clustering for grouping the pizzas.
upvoted 0 times
...
Bobbye
2 months ago
Pfft, linear regression for pizza grouping? What is this, amateur hour? K-means all the way, baby!
upvoted 0 times
...
Davida
2 months ago
I agree, K-means is definitely the right choice here. Gotta love that sweet, sweet clustering power!
upvoted 0 times
Jolanda
1 months ago
Agreed, K-means clustering is powerful for this type of data analysis.
upvoted 0 times
...
Eva
1 months ago
It's all about finding those center values and determining the distance from them.
upvoted 0 times
...
Margot
1 months ago
Definitely, K-means clustering will help us group the pizzas based on their properties.
upvoted 0 times
...
Elenor
1 months ago
K-means Clustering is the way to go for grouping those pizzas.
upvoted 0 times
...
...
Lachelle
2 months 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.
upvoted 0 times
Lajuana
2 months ago
Yes, K-means clustering is a great way to categorize the pizzas with similar characteristics.
upvoted 0 times
...
Isidra
2 months ago
I agree, K-means clustering would be the best technique to group the pizzas based on their properties.
upvoted 0 times
...
...

Save Cancel