Which of these is a potential limitation of using Decision Trees?Answer choicesSelect only one optionREVISITThey are computationally very expensive and slow to trainThey can easily overfit and won't always produce the best results when asked to generalizeThey are very unsuitable for regression tasksThey can only handle small datasets

Which of the following is/are the advantages(s) of decision tree?A) It requires little data preparationB) It can handle both categorical and numerical dataC) A small change in the training data will result in a large change in the treeAnswer choicesSelect only one optionREVISITOnly AA and BB and CA and C

Which of the following is a disadvantage of decision trees?Review LaterThey are computationally expensive to trainThey are prone to overfittingThey require labeled data for trainingThey are not suitable for high-dimensional data

Question 8What is an advantage of using Decision Trees over other machine learning methods?1 pointThey are simple to understand and interpret and can work on small datasets. They can be used for both classification and regression, whereas others are limited to one or the other.They can overfit datasets better than other methods because of the number of parameters learned.They allow for the processing of unstructured data, such as images and sequences of text.

What is a significant disadvantage of decision trees?Answer areaThey are difficult to interpretThey require a lot of dat preprocessingThey are prone to overfittingThey are not suitable for categorical data

What is a disadvantage of using a decision tree?Review LaterThey are not interpretableThey cannot handle large datasetsThey are prone to overfittingThey cannot be used for classification