Analysis Limitations
Among the major disadvantages of a decision tree analysis is its inherent limitations. The major limitations include:
Inadequacy in applying regression and predicting continuous values
Possibility of spurious relationships
Unsuitability for estimation of tasks to predict values of a continuous attribute
Difficulty in representing functions such as parity or exponential size
Possibility of duplication with the same sub-tree on different paths
Limited to one output per attribute, and inability to represent tests that refer to two or more different objects
An understanding of the pros and cons of a decision tree analysis reveals that decision tree disadvantages negate much of the advantages, especially in large and complex trees, inhibiting its widespread application as a decision-making tool.