Combining inductive and deductive tools for data analysis

In this paper we propose the combined use of different methods to improve t he data analysis process. This is obtained by combining inductive and deduc tive techniques. We also use different inductive techniques such as cluster ing algorithms, to derive data partition, and decision trees induction, cha racterizing classes in terms of logical rules. Inductive techniques are use d for generating hypotheses from data whereas deductive techniques are used to derive knowledge and to verify hypotheses. In order to guide users in t he analysis process, we have developed a system which integrates deductive tools and data mining tools such as classification algorithms, features sel ection algorithms, visualization tools and tools to manipulate data sets ea sily. The system developed is currently used in a large project whose aim i s the integration of information sources containing data concerning the soc ioeconomic aspects of Calabria and its subsequent analysis. Several experim ents on the socio-economic data have shown that the combined use of differe nt techniques improves both the comprehensibility and the accuracy of model s.