This paper is an overview of reconstructability analysis (RA), an approach to discrete multivariate modeling developed in the systems community. RA includes set‐theoretic modeling of relations and information‐theoretic modeling of frequency and probability distribution. It thus encompasses both statistical and nonstatistical problems. It overlaps with logic design and machine learning in engineering and with log‐linear modeling in the social sciences. Its generality gives it considerable potential for knowledge representation and data mining.
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