Topic 1 Question 223
3 つ選択A retail company wants to create a system that can predict sales based on the price of an item. A machine learning (ML) engineer built an initial linear model that resulted in the following residual plot:
Which actions should the ML engineer take to improve the accuracy of the predictions in the next phase of model building?
Downsample the data uniformly to reduce the amount of data.
Create two different models for different sections of the data.
Downsample the data in sections where Price < 50.
Offset the input data by a constant value where Price > 50.
Examine the input data, and apply non-linear data transformations where appropriate.
Use a non-linear model instead of a linear model.
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コメント(4)
- 正解だと思う選択肢: BEF
As per wolfsong said
👍 4stjokerli2023/03/12 - 正解だと思う選択肢: CDE
The residual plot shows that the linear model is not fitting the data well, with a clear pattern indicating that the model is underfitting. To improve the accuracy of the predictions, the ML engineer should take the following actions:
C. Downsample the data in sections where Price < 50: This could be an option since there seems to be a higher variance in the residuals in the region where Price < 50.
D. Offset the input data by a constant value where Price > 50: This could be an option since there seems to be a systematic bias in the residuals in the region where Price > 50.
E. Examine the input data, and apply non-linear data transformations where appropriate: This is necessary since the residual plot shows that the linear model is not capturing the non-linear relationships in the data.
👍 1AjoseO2023/02/20 - 正解だと思う選択肢: CDE
Two models , add a constant or in-put data transformation
👍 1Chelseajcole2023/03/01
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