CS431 - Machine Learning

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Across
  1. 2. Value of k in k-NN is determined using
  2. 4. L2 norm is also called as
  3. 7. is used to solve the dual optimization problem in SVM
  4. 9. Cost of k-means algorithm is measured using (abbreviated term)
  5. 10. What will be the size of the confusion matrix, if the dataset having 561 features with N class labels is used for training and testing?
  6. 11. Ratio of correctly predicted +ves to the total number of +ves is called
  7. 12. Representative objects used in the clustering method is termed to be
  8. 15. Method used to train the model with N-1 samples and tested with 1 sample
  9. 16. k-NN is an example of ___________ learning
  10. 20. Binary classifier sensitive to Noise?
  11. 22. Generalized distance measure of L1 and L2 norm is
  12. 25. Ratio of predicted +ves to the total number of predicted +ves
  13. 26. constant used to increase/decrease the net input value in logistic regression
  14. 27. P(X/C) in Naive Bayes is termed to be
  15. 29. Entropy of the dataset having binary class labels can have the value >1. State Yes or Noo
Down
  1. 1. Hair color is an example of ___________ data type
  2. 3. Class labels in the C4.5 algorithm are mostly at
  3. 5. refers to transforming the dimension of the data to a higher dimension for easy discrimination.
  4. 6. _________ method is used to handle continuous attribute in Naive Bayes
  5. 8. In the collected student dataset, scholarid of two students is missing, it can be replaced by a unique identifier. State Yes or Noo.
  6. 10. Sigmoid activation function transforms linear combined data to ______________ form.
  7. 13. soft margin SVM additionally has ________ variable with hard margin SVM
  8. 14. A classifier model performs better on training, but poorly on testing is referred to
  9. 17. ID3 is sensitive to number of ___________ attribute values
  10. 18. Iterative relocation is the other name of _________ algorithm
  11. 19. P(X) is naive bayes is termed to be
  12. 21. Distance measure used by k-NN to train and test the categorical features is
  13. 23. Non-linear Activation function
  14. 24. Type-I error in the confusion matrix refers to the value
  15. 28. Likert scale is an example of ___________ data