ELP-M2: An Efficient Model for Mining Least Patterns from Data Repository - Zailani, Abdullah; Amir, Ngah; Herawan, Tutut; Noraziah, Ahmad; Siti Zaharah, Mohamad; Abdul Razak, Hamdan (Springer, 2017)
Most of the algorithm and data structure facing a computational problem when they are required to deal with a highly sparse and dense dataset. Therefore, in this paper we proposed a complete model for mining least patterns known as Efficient Least Pattern Mining Model (ELP-M2) with LP-Tree data structure and LP-Growth algorithm. The comparative study is made with the well-know LP-Tree data structure and LP-Growth algorithm. Two benchmarked datasets from FIMI repository called Kosarak and T40I10D100K were employed. The experimental results with the first and second datasets show that the LP-Growth algorithm is more efficient and outperformed the FP-Growth algorithm at 14% and 57%, respectively.