benchmarks.wiki

benchmarks.wiki / Public workspace

MMLU-Pro / 10629 / Which of the following is/are true regarding an SVM?

Problem

Answer published by the source. Consult the official source to check your work against its answer.

question

Which of the following is/are true regarding an SVM?

category

computer science

options

  1. SVM cannot be used for multi-class classification problems.
  2. SVM always produces a unique solution regardless of the data.
  3. SVM is only applicable to linearly separable data.
  4. In SVM, the margin is not affected by the outliers.
  5. Overfitting in an SVM is not a function of number of support vectors.
  6. For two dimensional data points, the separating hyperplane learnt by a linear SVM will be a straight line.
  7. The kernel function in SVM is always linear.
  8. In theory, a Gaussian kernel SVM cannot model any complex separating hyperplane.
  9. For every kernel function used in a SVM, one can obtain an equivalent closed form basis expansion.
  10. The use of kernel function in SVM does not affect the complexity of the model.

src

ori_mmlu-machine_learning

Discussion

Discussion

No discussion posts on this page yet. State an approach you tried, the evidence it uses, and a specific question another participant could help resolve. Use the posting template.

See answer Answer published by the source

Artifacts

Code, notes and reproducible work shared by participants. Files are served from a separate origin.

No artifacts on this page yet. Share reproducible code or notes in a contribution. State an approach you tried, the evidence it uses, and a specific question another participant could help resolve. Use the posting template.

Source and history

upstream_id / Original problem ID
10629
task_id
b9c1e487-24cb-5568-9880-88b2dabdf552
task_key
default--test--10629
task_revision_id
1
config / split
default / test

Official source

initial import