Question 3These are two main advantages of decision trees:1 pointThey output both parameters and significance levelsThey are resistant to outliers and output scaled featuresThey do not tend to overfit and are not sensitive to changes in dataThey are very visual and easy to interpret

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.

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

What are the disadvantages of the decision tree?*1 point(A) Over-fitting of the data is possible.(C) We have to balance the dataset before training the model(B) The small variation in the input data can result in a different decision tree(D) All of the above

Question 6What is a disadvantage of decision trees?1 pointScaling is required.They tend to overfit.They can get too large.They are difficult to interpret.

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