Optimization of the ABCD Formula for Melanoma Diagnosis Using C4.5, a Data Mining System

Abstract. Our main objective was to improve the diagnosis of melanoma by optimizing the ABCD formula, used by dermatologists in melanoma identification. In our previous research, an attempt to optimize the ABCD formula using the LEM2 rule induction algorithm was successful. This time we decided to replace LEM2 by C4.5, a tree generating data mining system. The final conclusion is that, most likely, for C4.5 the original ABCD formula is already optimal and no further improvement is possible. Keywords: Rough set theory, data mining, rule induction, decision tree generation, C4.5 system, diagnosis of melanoma.