A new clustering algorithm was developed to improve how we group data with many attributes. By combining different clustering methods, the algorithm aims to be more accurate and faster for high-dimensional data. This approach helps overcome the challenges of complexity and accuracy that traditional methods face when dealing with lots of data attributes.