An implementation of logical analysis of data

The paper describes a new, logic-based methodology for analyzing observatio ns. The key features of the Logical Analysis of Data (LAD) are the discover y of minimal sets of features necessary for explaining all observations and the detection of hidden patterns in the data capable of distinguishing obs ervations describing "positive" outcome events from "negative" outcome even ts. Combinations of such patterns are used for developing general classific ation procedures. An implementation of this methodology is described in the paper along with the results of numerical experiments demonstrating the cl assification performance of LAD in comparison with the reported results of other procedures. In the final section, we describe three pilot studies on applications of LAD to oil exploration, psychometric testing, and the analy sis of developments in the Chinese transitional economy. These pilot studie s demonstrate not only the classification power of LAD, but also its flexib ility and capability to provide solutions to various case-dependent problem s.