AWS Certification Exam AI Practitioner (Practice Questions) set8

問題 65 / 65

In a predictive model that uses many features, some important variables are missing and errors are large in a specific patient group. What is the most likely cause?

Missing values are not being handled properly, causing bias.
Multicollinearity among features is making the model unstable.
The model isn't converging because the learning rate is too high.
The labels contain a lot of random noise.
The training data is overly normalized.

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