The diagnosis of incipient faults in power system elements such as transformers is usually based on the concentrations of dissolved gases existent in the insulation oil. There are consolidated DGA-based (dissolved gas analysis) methods in the literature, such as the Duval triangle. However, they present some limitations such as the existence of non-decision areas and erroneous results. Proposed is a simple methodology to improve the analysis of incipient faults based on rules extracted from a high-dimension space (21 attributes), formed by the gases concentrations and some of their interrelations. From such input space, the C4.5 method (decision tree) is used to extract a set of interpretable rules. Databases known in the DGA technical literature such as IEC TC 10 are adopted to analyse the proposed approach. When compared with a standard method, considering all data test folders in the performed 10-folder cross-validation statistical analysis, the extracted rules show greater accuracy with an error in the diagnosis of incipient faults of 6.25%, against 18.75% for the Triangle method in the worst case.