Relevant and non-redundant analytical information

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Abstract

Eckschlager, K. and Štěpánek, V., 1987. Relevant and non-redundant information. Chemometrics and Intelligent Laboratory Systems, 1: 273–284.

In the use of information obtained from a chemical analysis as grounds for decision making, not only its content but also its semantics are useful. Information that makes reliable decisions possible can be called relevant. As individual results obtained by a selective multi-component analysis need not be equally relevant for a given problem, we evaluate the exploitable amount of information as the sum of information contents of the analyses of individual components weighted by relevance coefficients, ki (0 ⩽ ki ⩽ 1). A relevance coefficient can be understood as a value of the membership function of information about the ith component to a fuzzy subset of relevant information. We either take ki as constants (a static model) or we consider relationships dki/dt = f(ki) (a dynamic model) where t is a quantity related to the information content.

In combining several methods, information redundance is taken into account and eliminated in evaluating the exploitable amount of information; thus relevant and non-redundant information is obtained.

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