What is a decision tree mainly used for in machine learning?Review LaterData CleaningFeature SelectionData ClassificationData Aggregation

What is the purpose of a decision tree in machine learning?Answer areaTo create a regression modelTo split data into subsets based on the value of input attributesTo perform clusteringTo reduce dimensionality

What is a decision tree algorithm used for?1 pointa. Classificationb. Regressionc. Clusteringd. Dimensionality reduction

What is a decision tree?Select one:a.A clustering algorithm used in unsupervised learningb.A linear model used to make predictions in supervised learningc.A neural network used in deep learningd.A tree-like model used to make predictions in supervised learning

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