👉 CDNA (Cumulative Distribution Network Analysis) is a mathematical framework used to analyze and visualize the complex relationships within large datasets, particularly in high-dimensional spaces. It extends traditional statistical methods by mapping data points onto a network graph, where nodes represent data points and edges signify the strength of relationships between them. The CDNA approach quantifies these relationships using a cumulative distribution function, which aggregates the influence of each data point across the network. This allows for a more intuitive and scalable understanding of data structure, enabling the identification of clusters, outliers, and patterns that might be obscured in higher-dimensional spaces. By leveraging graph theory and statistical techniques, CDNA provides a powerful tool for exploratory data analysis, machine learning, and visualization in fields like bioinformatics, social network analysis, and image processing.
