Algorithmic Features of Eclat

Nowadays basic algorithms such as Apriori and Eclat often are conceived as mere textbook examples without much practical applicability: in practice more sophisticated algorithms with better performance have to be used. We would like to challenge that point of view by showing that a carefully assembled implementation of Eclat outperforms the best algorithms known in the field, at least for dense datasets. For that we view Eclat as a basic algorithm and a bundle of optional algorithmic features that are taken partly from other algorithms like lcm and Apriori, partly new ones. We evaluate the performance impact of these different features and report about results of experiments that support our claim of the competitiveness of Eclat.

• Type: Conference
• Year: 2004
• Where: FIMI
• Authors: Lars Schmidt-Thieme
• Keywords: Algorithms, Basic Algorithm, Data Mining, FIMI 2004, Mere Textbook Examples