Question

What are the advantages of a decision tree classifier?

Answer 1

Below are the advantages of the Decision Tree classifier.

• Decision trees are able to produce understandable rules.
• They are able to handle both numerical and categorical attributes.
• They are easy to understand.
• Once a decision tree model has been built, classifying a test record is extremely fast.
• Decision tree depiction is rich enough to represent any discrete value classifier.
• Decision trees can handle datasets that may have errors.
• Decision trees can deal with handle datasets that may have missing values.
• They do not require any prior assumptions.  Decision trees are self-explanatory and when compacted they are also easy to follow. That is to say, if the decision tree has a reasonable number of leaves it can be grasped by non-professional users. Furthermore, since decision trees can be converted to a set of rules, this sort of representation is considered comprehensible.