21. Following are the types of supervised learning
22. overlearning causes due to an excessive . . . . . . . .
23. You trained a binary classifier model which gives very high accuracy on the training data, but much lower accuracy on validation data. Which is false.
24. For the given weather data, Calculate probability of playing
25. Which of the following is an example of a deterministic algorithm?
26. Gaussian Nave Bayes Classifier is . . . . . . . . distribution
27. In which of the following each categorical label is first turned into a positive integer and then transformed into a vector where only one feature is 1 while all the others are 0.
28. Simple regression assumes a . . . . . . . . relationship between the input attribute and output attribute.
29. The . . . . . . . . step eliminates the extensions of (k-1)-itemsets which are not found to be frequent,from being considered for counting support
30. Which of the following is true about weighted majority votes?
1. We want to give higher weights to better performing models
2. Inferior models can overrule the best model if collective weighted votes for inferior models is higher than best model
3. Voting is special case of weighted voting
1. We want to give higher weights to better performing models
2. Inferior models can overrule the best model if collective weighted votes for inferior models is higher than best model
3. Voting is special case of weighted voting
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