SVM(Support Vector Machine)

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Across
  1. 2. The primary task where SVM is used to assign labels to inputs
  2. 6. A decision boundary that separates data into classes
  3. 7. A commonly used kernel that handles non-linear relationships
  4. 8. Allows some misclassification to handle non-separable data
  5. 9. The distance between the separating hyperplane and the closest data points
Down
  1. 1. A modeling error when a model learns noise instead of pattern
  2. 3. A type of SVM that works when data is linearly separable
  3. 4. Data points that lie closest to the decision boundary
  4. 5. A function that transforms data into higher-dimensional space