According to the territorial-regional development policy of Russia, a rigid structuring of the country's space is applied through the prism of a hierarchical management system. As a result, the structure of the space of the entire country was fixed through a system of boundaries, the markers of which highlight management objects at the national level, subject of the Russian Federation, territory, region, district. This article will present the main stereotypes that influence the creation of the perception of new territories in the nature of marginality. As is known, the formation of marginal communities can be traced throughout the history of civilizations. It is important to separate geographical marginality from spatial marginality. In geography, there is the concept of “marginal territories”, which can be considered those located on the remote periphery of the region or in isolated places. Such a phenomenon as spatial marginality is characterized precisely by the prevailing stereotypes in society about a specific area. Urban spatial perception critically influences human behavior and emotional responses, emphasizing the need to align urban spaces with human needs to improve the quality of urban life. However, the classification of urban architecture based on functionality is subject to biases stemming from discrepancies between objective representation and subjective perception. These biases can lead to city planning and designs that fail to adequately meet the needs and preferences of city residents, negatively impacting their quality of life and the overall functionality of the city. In this study, we apply machine learning to uncover these biases in urban spatial perception research using a three-step methodology: objective mapping, subjective perception analysis, and perceptual bias assessment. Our results show that machine learning can reveal hidden patterns in this area of research with significant implications for urban planning and design. Of particular note, the study found significant discrepancies in the distribution centroids between commercial buildings and residential or public buildings. This result sheds light on the spatial organization characteristics of urban architectural functions, serving as a valuable guide for urban planning and development. Moreover, it reveals the advantages and disadvantages of different data sources and methods for interpreting urban spatial perception, paving the way to a more complete understanding of the subject. These results highlight the importance of integrating both objective mapping and subjective perspectives when classifying the functionality of urban architecture.