Deal of The Day! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions

Microsoft Exam DP-100 Topic 9 Question 100 Discussion

Actual exam question for Microsoft's DP-100 exam
Question #: 100
Topic #: 9
[All DP-100 Questions]

You are building recurrent neural network to perform a binary classification.

The training loss, validation loss, training accuracy, and validation accuracy of each training epoch has been provided. You need to identify whether the classification model is over fitted.

Which of the following is correct?

Show Suggested Answer Hide Answer
Suggested Answer: B

Contribute your Thoughts:

Frank
2 months ago
Option B is the answer, no doubt about it. It's just like my grandma used to say, 'If the training loss is down and the validation's up, your model's in a rut!'
upvoted 0 times
Gregg
14 days ago
I agree, that indicates the model is overfitting.
upvoted 0 times
...
Nan
22 days ago
I think option B is correct. The training loss decreases while the validation loss increases.
upvoted 0 times
...
Antonio
25 days ago
'If the training loss is down and the validation's up, your model's in a rut!'
upvoted 0 times
...
Luisa
27 days ago
Option B is the answer, no doubt about it.
upvoted 0 times
...
...
Ethan
2 months ago
Hmm, this is a tricky one. I'm going to have to think about it more. Maybe I should ask the professor to give me a hint - I heard they're quite fond of dad jokes.
upvoted 0 times
...
Celeste
2 months ago
I agree with Nickolas. Option B is the way to identify overfitting in a binary classification model.
upvoted 0 times
Karma
8 days ago
Exactly. It's important to monitor these metrics to prevent overfitting in the model.
upvoted 0 times
...
Shala
23 days ago
So, if the validation loss is increasing while the training loss is decreasing, it means the model is overfitting.
upvoted 0 times
...
Vannessa
1 months ago
I agree with you. That's a sign of overfitting in a binary classification model.
upvoted 0 times
...
Jade
1 months ago
I think option B is correct. The training loss decreases while the validation loss increases when training the model.
upvoted 0 times
...
...
Nickolas
2 months ago
Option B seems correct to me. When the model is overfitting, the training loss decreases while the validation loss increases.
upvoted 0 times
...
Luis
2 months ago
Why do you think D is the correct answer?
upvoted 0 times
...
Jettie
2 months ago
I disagree, I believe the correct answer is D.
upvoted 0 times
...
Luis
2 months ago
I think the correct answer is B.
upvoted 0 times
...

Save Cancel