MLS-C01 Web TestEngine Demo

Q32 Single choice

A company is building a predictive maintenance model for its warehouse equipment. The model must predict the probability of failure of all machines in the warehouse. The company has collected 10,000 event samples within 3 months. The event samples include 100 failure cases that are evenly distributed across
50 different machine types.

How should the company prepare the data for the model to improve the model's accuracy?

A
Adjust the class weight to account for each machine type.
B
Oversample the failure cases by using the Synthetic Minority Oversampling Technique (SMOTE).
C
Undersample the non-failure events. Stratify the non-failure events by machine type.
D
Undersample the non-failure events by using the Synthetic Minority Oversampling Technique (SMOTE).

MLS-C01 Web TestEngine demo