In his 2004 paper, "Non-negative Matrix Factorization with Sparseness Constraints," Patrick Hoyer introduced a function that measures the sparseness of a nonzero vector. The paper does not explain or motivate the formula, so this article describes the geometry and intuition behind Hoyer's formula, along with a visualization and examples. Hoyer's
Consider the following quote from George Box: “All models are wrong, some are useful.” Most of today’s models are free. And models power AI outcomes. When considering your enterprise strategy, AI should fit snuggly into business processes that successfully execute tasks supporting the overall strategic vision – underwriting policies, pricing
Explore how SAS Health and SAS Viya help healthcare organizations transform clinical and operational data into predictive, AI-driven decisioning workflows that improve patient outcomes through risk identification, model deployment, and governed agentic AI.
