Incorrect answer to question.

[rojones]

Good Day.

I was working through the Section-Based – Exploratory Data Analysis (Machine Learning) and came across the question below.

“A Machine Learning Specialist has various CSV training datasets stored in an S3 bucket. Previous models trained with similar training data size using the Amazon SageMaker XGBoost algorithm have a slow training process. The Specialist wants to decrease the amount of time spent on training the model.

Which combination of steps should be taken by the Specialist? (Select TWO.)“

The answer was given as CSV in Pipe mode or RecordIO Protobuf. But XGboost dose not support Pipe mode nor does it support RecordIO.

https://docs.aws.amazon.com/sagemaker/latest/dg/xgboost.html

[Carlo-TutorialsDojo]

Hello rojones,

Thanks for your feedback. Much appreciated.

Yes, the XGBoost algorithm only supports text/csv and txt/libsvm content types which makes the question incorrect. We will refactor the scenario so it’ll be aligned to the given answer.

Thanks & Regards,

Carlo @ Tutorials Dojo

[MichaelRForrester]

Hi…. I may have another at least the explanation…

A Machine Learning Specialist is training a binary classification model for a particular business use case. To help the Specialist in choosing the most optimal model, the company has given the following conditions that must be satisfied:

Choose the most cost-effective model given that false negatives are 3 times more expensive than false positives.

Choose the model with a recall rate of 85% or more.

Choose the model with a false negative rate of 15% or less.

The Specialist has generated a confusion matrix for each model for evaluation.

Which of the following confusion matrices meets the business requirements?

Answer is correct…

but the formula for Recall

To correctly answer this problem, we have to know three formula:

Recall = TP / (TP/FN)

False Negative Rate = FN / (FN+TP)

Should that be Recall = TP / (TP + FN) just checking

[Carlo-TutorialsDojo]

Hello Michael,

Thanks for pointing this out. It’s a typo. You’re right, the formula should be Recall = TP / (TP+FN).

We will correct this.

Let me know if you have any other questions.

Regards,

Carlo @ Tutorials Dojo