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Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 All Questions

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Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 topic 1 question 35 discussion

Exam question from Amazon's AWS Certified Machine Learning Engineer - Associate MLA-C01
Question #: 35
Topic #: 1
[All AWS Certified Machine Learning Engineer - Associate MLA-C01 Questions]

A company is using ML to predict the presence of a specific weed in a farmer's field. The company is using the Amazon SageMaker linear learner built-in algorithm with a value of multiclass_dassifier for the predictorjype hyperparameter.
What should the company do to MINIMIZE false positives?

  • A. Set the value of the weight decay hyperparameter to zero.
  • B. Increase the number of training epochs.
  • C. Increase the value of the target_precision hyperparameter.
  • D. Change the value of the predictorjype hyperparameter to regressor.
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Suggested Answer: C 🗳️
by GiorgioGss at Nov. 27, 2024, 10:15 p.m.
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Saransundar
1 month, 2 weeks ago
Selected Answer: C
A. Weight decay = 0 → No regularization, doesn’t target false positives. B. More epochs → Longer training, risks overfitting, no direct impact on false positives. C. Higher precision → Prioritizes correct positives, reduces false positives. D. Regressor → Predicts continuous values, unsuitable for classification.
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GiorgioGss
1 month, 3 weeks ago
Selected Answer: C
https://docs.aws.amazon.com/sagemaker/latest/dg/ll_hyperparameters.html
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