The correct answer is: C. both options except none
Tree-based classifiers are a type of supervised machine learning algorithm that can be used to classify data. They work by creating a tree-like structure, where each node in the tree represents a decision that needs to be made to classify an instance. The leaves of the tree represent the possible classes that an instance can belong to.
To classify an instance, the tree is traversed from the root node to a leaf node, following the decisions made at each node. The class associated with the leaf node is then assigned to the instance.
Tree-based classifiers are often used for classification tasks where the data is not well-structured or where there are a large number of possible classes. They are also relatively easy to interpret, which can be helpful in understanding how the algorithm is making its decisions.
Here is a more detailed explanation of each option:
- A. classifiers which form a tree with each attribute at one level
This is a correct description of tree-based classifiers. The tree-like structure of a tree-based classifier is created by recursively splitting the data into smaller and smaller subsets. Each split is made on the basis of a single attribute, and the leaves of the tree represent the possible classes that an instance can belong to.
- B. classifiers which perform series of condition checking with one attribute at a time
This is also a correct description of tree-based classifiers. The decision-making process in a tree-based classifier can be thought of as a series of condition checks, where each condition check is based on a single attribute. The instance is then assigned to the class that is associated with the leaf node that is reached at the end of the decision-making process.
- C. both options except none
This is the correct answer. Tree-based classifiers are both classifiers which form a tree with each attribute at one level and classifiers which perform series of condition checking with one attribute at a time.
- D. not possible
This is an incorrect answer. Tree-based classifiers are both classifiers which form a tree with each attribute at one level and classifiers which perform series of condition checking with one attribute at a time.