Topic 1 Question 35
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?
Set the value of the weight decay hyperparameter to zero.
Increase the number of training epochs.
Increase the value of the target_precision hyperparameter.
Change the value of the predictorjype hyperparameter to regressor.
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- 正解だと思う選択肢: C👍 1GiorgioGss2024/11/27
- 正解だと思う選択肢: 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.
👍 1Saransundar2024/12/04
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