The paper considers a problem of defining the importance of asked questions for the examinee under judicial and psychophysiological polygraph examination by methods of mathematical statistics. It offers the classification algorithm based on the logistic regression as an optimum Bayesian classifier, considering weight coefficients of information for the polygraph-recorded physiological parameters with no condition for independence of the measured signs.

Actually, binary classification is executed by results of polygraph examination with preliminary normalization and standardization of primary results, with check of a hypothesis that distribution of obtained data is normal, as well as with calculation of coefficients of linear regression between input values and responses by method of maximum likelihood. Further, the logistic curve divided signs into two classes of the "significant" and "insignificant" type.

Efficiency of model is estimated by means of the ROC analysis (Receiver Operator Characteristics). It is shown that necessary minimum sample has to contain results of 45 measurements at least. This approach ensures a reliable result provided that an expert-polygraphologist possesses sufficient qualification and follows testing techniques.