The correct answer is A. greedy.
A greedy algorithm is an algorithm that always makes the choice that seems best at the moment, without considering the consequences of future choices. This can lead to suboptimal solutions, but it can also be very efficient.
In decision tree induction, the greedy algorithm starts with a single node, which represents the entire set of data. At each step, the algorithm chooses the feature that best splits the data into two subsets. This process is repeated until each subset contains only one class.
The greedy algorithm is a simple and efficient way to build decision trees. However, it can sometimes lead to suboptimal solutions. There are other algorithms for decision tree induction that are more complex but can produce better results.
The other options are incorrect.
- B. top down is not the approach of basic algorithm for decision tree induction. Top-down induction is a type of machine learning that builds a model by starting with a general hypothesis and then making more specific hypotheses as more data is collected. This is in contrast to bottom-up induction, which starts with specific hypotheses and then combines them into more general hypotheses.
- C. procedural is not the approach of basic algorithm for decision tree induction. A procedural algorithm is a type of algorithm that is written in a step-by-step fashion. This is in contrast to declarative algorithms, which are written in a more abstract fashion.
- D. step by step is not the approach of basic algorithm for decision tree induction. Step-by-step is a way of describing something that happens in a series of small steps. This is not the same as the approach of basic algorithm for decision tree induction.