Question

A decision tree is pruned in order to:
A. improve classification accuracy on training set
B. improve generalization performance
C. reduce dimensionality of the data
D. make the tree balanced

Answer 1

answer:

A.

Explanation:

A.improve classification accuracy on training set

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Answer 2

A decision tree is pruned in order to:

A. improve classification accuracy on training set

B. improve generalization performance

C. reduce dimensionality of the data

D. make the tree balanced

The correct answer is :

C. reduce dimensionality of the data

Explanation :

A decision tree helps to reduce the dimensionality of the data. A decision tree is a structure that is made using algorithms for learning for the purpose of classification and regression. One of the problems we face when learning a decision tree is to learn the optimal shape of the resulting tree, which leads to better accuracy of the model.

A decision tree tends to have too many branches and layers, which can lead to data overfitting. Therefore, to reduce the dimensionality of the data, decision tree pruning is done, so that the dimensionality of the data can be reduced.

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