A decision tree is a diagram consisting of:Group of answer choicescircular decision nodes, square probability nodes, and branches.square decision nodes, circular probability nodes, and branches.any shapes and form that the analyst chooses.branches with angles and distance indicating the likelihood of branch selection.

What is a decision tree?Question 8Answera.A neural network used in deep learningb.A linear model used to make predictions in supervised learningc.A clustering algorithm used in unsupervised learningd.A tree-like model used to make predictions in supervised learning

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

In a decision tree arrows coming out of which nodes have probability values associated?

What does the term "terminal node" refer to in a decision tree?A:    The node responsible for choosing the best-split pointB:    This node is also known as a leaf node, and is usually accompanied by a potential output valueC:    The node at the top of the tree where decision-making startsD:    Any node that splits the data into two subsets

Suppose you're creating a beginner's guide to decision tree algorithms for a data science blog. How would you compare and contrast the terms "root node," "leaf node," and "branch" to your readers, ensuring they understand the fundamental components and structure of decision trees?