THE METHOD OF DEVELOPING A CLASSIFIER USING THE BAYES THEOREM FOR MAKING A DECISION ON THE DETERMINATION OF TRUE INFORMATION

The range of application of cluster analysis is very wide: it is used in archeology, medicine, psychology, biology, public administration, regional economy, marketing, sociology and other disciplines. Each discipline has its own requirements for primary data and rules for forming groups. Obviously, there will be different methodological approaches to market segmentation, the purpose of which is to identify groups of objects that are similar in terms of features and properties and to the formation of clusters that unite to strengthen their competitive advantages. Thus, when processing information in the information space, the methodology is usually aimed at building a mathematical model of cluster analysis of the object or phenomenon under study, and even obtaining an answer to the question: "Is the information true or not." Detecting false information in the digital world is an important task in overcoming the widespread spread of rumors and prejudices. The paper analyzes the existing methods of information classification in the information age. Formulate the signs of the information age, in the context of determining the veracity of information. Based on the main features of the