PolyAnalyst - A Machine Discovery System Inferring Functional Programs

The present paper describes the learning technique used in PolyAnalyst - the system of machine discovery and intelligent analysis of the experimental/observational data which has been created in the Computer Patient Monitoring Laboratory at the National Research Center of Surgery. PolyAnalyst is a multi-purpose system designed to solve the following classes of problems: 1) construction of a procedure realizing the mapping from the set of descriptions to the set of parameters given by the pairs ; 2) search for the interdependences between components of the description; 3) search for characteristic features of a given set of descriptions. Here the description means a single experimental/observational data record and it is assumed that all the records in the same set of observations have the same structure. The paper is devoted mainly to PolyAnalyst's application to the type 1 problems. This type includes classification, empirical law inference, choice of the best decision from a fixed set of possible decisions, and other tasks. To solve a problem PolyAnalyst constructs and tests programs on a simple functional programming language whose inputs are the descriptions and outputs are the corresponding parameter values. While searching for the solution PolyAnalyst combines full search, heuristical search, and direct construction of the programs. Since the first version of PolyAnalyst was created it has solved a number of real problems from chemistry, medicine, geophysics, and agricultural science. One example is given in the paper - the prediction of the elasticity of the polyethylene samples from their infra-red spectrums.

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