32.
. . . . . . . . is the most drastic one and should be considered only when the dataset is quite large, the number of missing features is high, and any prediction could be risky.

34.
Which of the following is true about averaging ensemble?

35.
Which of the following parameters can be tuned for finding good ensemble model in bagging based algorithms?
1. Max number of samples
2. Max features
3. Bootstrapping of samples
4. Bootstrapping of features

36.
Which one of the following is not a major strength of the neural network approach?

37.
Given above is a description of a neural network. When does a neural network model become a deep learning model?

38.
Which of the following metrics, do we have for finding dissimilarity between two clusters in hierarchical clustering?
1. Single-link
2. Complete-link
3. Average-link

40.
Having built a decision tree, we are using reduced error pruning to reduce the size of the tree. We select a node to collapse. For this particular node, on the left branch, there are 3 training data points with the following outputs: 5, 7, 9.6 and for the right branch, there are four training data points with the following outputs: 8.7, 9.8, 10.5, 11. What were the original responses for data points along the two branches (left & right respectively) and what is the new response after collapsing the node?

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