Question 1These are all characteristics of decision trees, EXCEPT:1 pointThey have well rounded decision boundariesThey split nodes into leavesThey can be used for either classification or regressionThey segment data based on features to predict results

Question 2When splitting data into branches for a decision tree, what kind of feature is favored and chosen first?1 pointThe feature that increases purity in the tree nodes.The feature with the greatest number of categories.The feature that splits the data equally into groups.The feature that increases entropy in the tree nodes.

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

Which of the following are the advantage/s of Decision Trees? Tick all the correct options.3 pointsPossible Scenarios can be addedUse a white box model, If given result is provided by a modelWorst, best and expected values can be determined for different scenariosAll of the above

Which of the following statements is not true about the Decision tree?1 pointa) It starts with a tree with a single leaf and assign this leaf a label according to a majority vote among all labels over the training setb) It performs a series of iterations and on each iteration, it examine the effect of splitting a single leafc) It defines some gain measure that quantifies the improvement due to the splitd) Among all possible splits, it either choose the one that minimizes the gain and perform it, or choose not to split the leaf at all

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