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Question 191 - MLS-C01 discussion

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A logistics company needs a forecast model to predict next month's inventory requirements for a single item in 10 warehouses. A machine learning specialist uses Amazon Forecast to develop a forecast model from 3 years of monthly data. There is no missing data. The specialist selects the DeepAR+ algorithm to train a predictor. The predictor means absolute percentage error (MAPE) is much larger than the MAPE produced by the current human forecasters.

Which changes to the CreatePredictor API call could improve the MAPE? (Choose two.)

A.
Set PerformAutoML to true.
Answers
A.
Set PerformAutoML to true.
B.
Set ForecastHorizon to 4.
Answers
B.
Set ForecastHorizon to 4.
C.
Set ForecastFrequency to W for weekly.
Answers
C.
Set ForecastFrequency to W for weekly.
D.
Set PerformHPO to true.
Answers
D.
Set PerformHPO to true.
E.
Set FeaturizationMethodName to filling.
Answers
E.
Set FeaturizationMethodName to filling.
Suggested answer: A, D

Explanation:

The MAPE of the predictor could be improved by making the following changes to the CreatePredictor API call:

Set PerformAutoML to true. This will allow Amazon Forecast to automatically evaluate different algorithms and choose the one that minimizes the objective function, which is the mean of the weighted losses over the forecast types.By default, these are the p10, p50, and p90 quantile losses1. This option can help find a better algorithm than DeepAR+ for the given data.

Set PerformHPO to true. This will enable hyperparameter optimization (HPO), which is the process of finding the optimal values for the algorithm-specific parameters that affect the quality of the forecasts.HPO can improve the accuracy of the predictor by tuning the hyperparameters based on the training data2.

The other options are not likely to improve the MAPE of the predictor. Setting ForecastHorizon to 4 will reduce the number of time steps that the model predicts, which may not match the business requirement of predicting next month's inventory. Setting ForecastFrequency to W for weekly will change the granularity of the forecasts, which may not be appropriate for the monthly data. Setting FeaturizationMethodName to filling will not have any effect, since there is no missing data in the dataset.

References:

CreatePredictor - Amazon Forecast

HPOConfig - Amazon Forecast

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asked 16/09/2024
Loyston Mathias
41 questions
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