Comparative Investigations and Performance Evaluation for Multiple-Level Association Rules Mining Algorithm

This paper focuses on the comparative investigation and performance evaluation of the ML_TMLA algorithm that generates multiple transaction tables for all levels in one database scan with that of ML_T2L1 and ML_T1LA algorithms. The performance study has been carried out on different kinds of data distributions (three synthetic and one real dataset) and thresholds that identify the conditions for algorithm selection. The AR Tool has been used for the experimental and comparative evaluation of the proposed algorithm with other algorithms.