Machine Learning MCQs with answers Page - 8

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Q. What is the Accuracy in percentage based on following confusion matrix of three class classification. Confusion Matrix C= [14 0 0] [ 1 15 0] [ 0 0 6]

  • (A) 0.75
  • (B) 0.97
  • (C) 0.95
  • (D) 0.85

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Q. Suppose you are using RBF kernel in SVM with high Gamma value. What does this signify?

  • (A) The model would consider even far away points from hyperplane for modeling
  • (B) The model would consider only the points close to the hyperplane for modeling
  • (C) The model would not be affected by distance of points from hyperplane for modeling
  • (D) None of the above

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Q. The difference between the actual Y value and the predicted Y value found using a regression equation is called the

  • (A) slope
  • (B) residual
  • (C) outlier
  • (D) scatter plot

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Q. Which of the following method is used for multiclass classification?

  • (A) one vs rest
  • (B) loocv
  • (C) all vs one
  • (D) one vs another

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Q. To determine association rules from frequent item sets

  • (A) only minimum confidence needed
  • (B) neither support not confidence needed
  • (C) both minimum support and confidence are needed
  • (D) minimum support is needed

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Q. The objective of the support vector machine algorithm is to find a hyperplane in an N-dimensional space(N the number of features) that distinctly classifies the data points.

  • (A) TRUE
  • (B) collinerity
  • (C) ---
  • (D) ---

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Q. What does dimensionality reduction reduce?

  • (A) stochastics
  • (B) not frequent
  • (C) performance
  • (D) entropy

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Q. Like the probabilistic view, the . . . . . . . . view allows us to associate a probability of membership with each classification.

  • (A) exampler
  • (B) analogy
  • (C) classical
  • (D) inductive

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Q. Hierarchical agglomerative clustering is typically visualized as?

  • (A) dendrogram
  • (B) binary trees
  • (C) block diagram
  • (D) graph

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Q. Commons unsupervised applications include

  • (A) object segmentation
  • (B) similarity detection
  • (C) automatic labeling
  • (D) all above