Description: Perceptual Clustering is a data grouping method that relies on human perception to organize and classify information. Unlike traditional clustering methods, which focus on mathematical and statistical characteristics of data, Perceptual Clustering considers how humans perceive and categorize information. This approach is particularly relevant in contexts where human interpretation plays a crucial role, such as image analysis, text classification, or market segmentation. The main features of Perceptual Clustering include the incorporation of subjective factors, such as visual similarity or contextual relevance, allowing for a grouping that is more aligned with the end user’s experience. This method aims not only to group data efficiently but also to do so in a way that makes sense from the user’s perspective. The relevance of Perceptual Clustering lies in its ability to enhance usability and interpretation of results in practical applications, making data more accessible and understandable for humans. As the amount of data increases exponentially, this approach becomes increasingly valuable for facilitating informed decision-making and understanding complex patterns across various domains.
