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Câu 88: AWS Certified Machine Learning - Specialty (MLS-C01)

A Machine Learning Specialist is applying a linear least squares regression model to a dataset with 1,000 records and 50 features. Prior to training, the MLSpecialist notices that two features are perfectly linearly dependent. Why could this be an issue for the linear least squares regression model?

Nội dung câu hỏi

A Machine Learning Specialist is applying a linear least squares regression model to a dataset with 1,000 records and 50 features. Prior to training, the MLSpecialist notices that two features are perfectly linearly dependent. Why could this be an issue for the linear least squares regression model?

Các lựa chọn

Đáp án được giữ gọn theo nhãn A, B, C, D trong phần bình chọn tương tác.

  1. A. It could cause the backpropagation algorithm to fail during training
  2. B. It could create a singular matrix during optimization, which fails to define a unique solution — đáp án hiện tại
  3. C. It could modify the loss function during optimization, causing it to fail during training
  4. D. It could introduce non-linear dependencies within the data, which could invalidate the linear assumptions of the model

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