Classification Rules Obtained from Evidence Accumulation

This paper presents a machine learning approach applicable to Data Mining based on obtaining classification rules. It proposes a strategy to obtain classification rules from clusters resulting from a co-association matrix. Such matrix is obtained from the combination of different clustering methods applied to input data, and it has been selected by its result´s robustness. The proposed method has been applied to two sets of data obtained from the UCl repository with really successful results. The results obtained in the classification have been compared to other existing methods showing the new proposed method superiority.