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

- Free Preparation Discussions

Databricks Exam Databricks-Certified-Professional-Data-Scientist Topic 5 Question 66 Discussion

Actual exam question for Databricks's Databricks-Certified-Professional-Data-Scientist exam
Question #: 66
Topic #: 5
[All Databricks-Certified-Professional-Data-Scientist Questions]

You are working on a email spam filtering assignment, while working on this you find there is new word e.g. HadoopExam comes in email, and in your solutions you never come across this word before, hence probability of this words is coming in either email could be zero. So which of the following algorithm can help you to avoid zero probability?

Show Suggested Answer Hide Answer
Suggested Answer: B

Contribute your Thoughts:

Pearline
3 months ago
Naive Bayes is good too, but Laplace Smoothing is specifically designed to handle zero probabilities.
upvoted 0 times
...
Phyliss
3 months ago
But what about Naive Bayes? Wouldn't that also be a good choice?
upvoted 0 times
...
Darrel
3 months ago
I agree with Pearline, Laplace Smoothing can help avoid zero probability.
upvoted 0 times
...
Donte
3 months ago
Laplace Smoothing, got it. I'm just glad I don't have to deal with the 'HadoopExam' word in my emails. That sounds like a whole other problem!
upvoted 0 times
...
Emerson
3 months ago
Wow, who knew spam filtering could be so complex? Laplace Smoothing seems like the way to go. It's like a superhero for my email inbox.
upvoted 0 times
Heike
2 months ago
It's definitely a superhero for your email inbox, helping to avoid zero probability for new words like HadoopExam.
upvoted 0 times
...
Ricki
2 months ago
Yes, Laplace Smoothing is a great technique to handle unseen words in email spam filtering.
upvoted 0 times
...
...
Pearline
3 months ago
I think the answer is B) Laplace Smoothing.
upvoted 0 times
...
Tien
3 months ago
Hmm, Laplace Smoothing, huh? Sounds fancy. I bet it's like the baking soda of the spam filtering world - just a pinch makes everything better.
upvoted 0 times
Royal
2 months ago
Naive Bayes, Laplace Smoothing, and Logistic Regression can all help with that.
upvoted 0 times
...
Corinne
2 months ago
It helps avoid zero probability for new words like HadoopExam.
upvoted 0 times
...
Malika
2 months ago
Yes, Laplace Smoothing is like adding a pinch of baking soda to improve the spam filtering.
upvoted 0 times
...
...
Lasandra
3 months ago
Laplace Smoothing all the way! It's like a secret ingredient that makes your spam filter tasty, even when there's a new spice in the mix.
upvoted 0 times
Leonie
2 months ago
All of the above algorithms are great, but Laplace Smoothing really stands out in this scenario.
upvoted 0 times
...
Tina
2 months ago
I agree, it helps avoid those zero probabilities and keeps the filter accurate.
upvoted 0 times
...
Danilo
2 months ago
It's like a safety net for those unexpected words like HadoopExam.
upvoted 0 times
...
Malcolm
3 months ago
Laplace Smoothing is definitely the way to go.
upvoted 0 times
...
...

Save Cancel