The correct answer is C. both a and b.
A decision tree is a tree-like structure that is used to make decisions. The tree is made up of nodes, which represent different possible choices, and edges, which represent the consequences of those choices. The leaves of the tree represent the possible outcomes of the decision.
Decision trees are often used in machine learning to classify data. In this case, the nodes of the tree represent different features of the data, and the edges represent the values of those features. The leaves of the tree represent the different classes that the data can be classified into.
Decision trees can also be used to make predictions. In this case, the nodes of the tree represent different variables, and the edges represent the values of those variables. The leaves of the tree represent the possible values of the variable that is being predicted.
Decision trees are a powerful tool for making decisions and predictions. They are easy to understand and interpret, and they can be used to solve a variety of problems.
Here is a more detailed explanation of each option:
- Option A: A flow-chart is a diagram that shows the steps in a process. It is often used to represent the logic of a computer program. Flow-charts can be simple or complex, but they always have a starting point, a series of steps, and an ending point.
- Option B: A structure in which internal node represents test on an attribute, each branch represents outcome of test and each leaf node represents class label. This is a more detailed description of what a decision tree is. As mentioned above, a decision tree is a tree-like structure that is used to make decisions. The tree is made up of nodes, which represent different possible choices, and edges, which represent the consequences of those choices. The leaves of the tree represent the possible outcomes of the decision.
- Option C: both a and b. This is the correct answer. A decision tree is both a flow-chart and a structure in which internal node represents test on an attribute, each branch represents outcome of test and each leaf node represents class label.
- Option D: none of the above. This is the incorrect answer. A decision tree is both a flow-chart and a structure in which internal node represents test on an attribute, each branch represents outcome of test and each leaf node represents class label.