Fayyad's Algorithm

Fayyad's Algorithm is a method used in data analysis to identify meaningful groups or patterns within large datasets. It works by first dividing the data into smaller segments, then analyzing each segment to find significant internal structures. These segments are then combined iteratively to form larger, more comprehensive clusters until the entire dataset is organized into a hierarchy of related groups. This process helps uncover underlying patterns or categories within complex data, making it easier to interpret and analyze, especially in fields like pattern recognition and machine learning.