Abstract
Problem definition. Many artificial intelligence systems are essentially event classification systems. They are widely used in predictive analytics. Their role as predictors of hazardous events in transportation is constantly growing. The efficient application of artificial intelligence methods largely depends on the results of misclassification. Therefore, the problem associated with the calculation or statistical evaluation of the probability of misclassification and boundary value definition is of relevance. Aim. To estimate the boundaries for the combined probability of misclassification due to two different categories of errors, i.e., misclassifications proper and statistical errors resulting from misclassification. Results. The threshold value that is used for classification was statistically evaluated. The boundary conditions for the combined probability of misclassification were established. A generalization for N-dimensional spaces and general distributions and shapes of threshold surfaces was presented. The theoretical findings were illustrated with an example of practical application.
Published Version
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