The M5 algorithm is a hybrid model that combines Decision Trees generated by the Iterative Dichotomiser 3 (ID3) algorithm with Regression Models. It uses a decision tree to discretize the input space and then fits regression models in the resulting partitions, leading to improved predictive accuracy.


  • By utilizing decision trees for discretization and incorporating regression models, the M5 algorithm offers improved predictive performance and flexibility for handling both categorical and continuous data.
  • The M5 algorithm is known for its capability to manage both numerical and nominal attributes, making it suitable for a wide range of Predictive Analysis tasks.
  • the M5 algorithm is commonly employed in modeling scenarios where both Classification and Regression tasks exist within the same dataset.