Building LP-Risk Model of LP-Classification Class

Abstract

The real logic of our world is the calculation of probabilities. Maxwell For the construction of logic and probabilistic (LP) risk models of the LP-classification class we formulate identification tasks on statistic data, describe peculiarities and methods of identification and iterative algorithms, carry out research results, estimate computational complexity of algorithms and accuracy of training and testing LP-risk models.The identification of the LP-risk model was the first and, perhaps, the most difficult task, solved for economics and it had all the basic components of the intelligent, information, innovative technologies. The problems of building LP-risk model of LP-classification class are important a number of reasons. The classification problem (objects, system states, companies, banks, countries) is one of the basic ones in science and is solved by statistical data. We build knowledge bases as a system of logical equations. We transit to the LP-risk model of this class broadening the possibilities for LP-models of the classes LP-efficiency and LP-forecasting for solving the tasks of analysis and management.KeywordsOptimal AsymmetryGood CreditAverage Risk ValueSamples Vib1Asymmetric TrainingThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.