Abstract: Spectral clustering algorithms rely on graphs where edges are defined based on the similarity between the vertices (data points). The effectiveness and fairness of spectral clustering depend ...
Advanced K-Means clustering system for customer analytics and segmentation using machine learning. Includes RFM analysis, business insights, and actionable marketing strategies. - ...
Python API for reading WINISI .cal files (spectral data files used in NIR applications). The feature should enable users to extract spectral data, sample information, and metadata from .cal files. It ...
WEST LAFAYETTE, Ind. — Professionals in agriculture, defense and security, environmental monitoring, food quality analysis, industrial quality control, and medical diagnostics could benefit from a ...
Abstract: Traditional spectral clustering methods struggle with scalability and robustness in large datasets due to their reliance on similarity matrices and EigenValue Decomposition. We introduce two ...
Even for the world’s largest carnivorous bat, a hug is the best hello. Spectral bats are far more cooperative than researchers long assumed, routinely greeting one another with wing wraps and even ...
A startling milestone has been reached in Florida's war against the invasive Burmese pythons eating their way across the Everglades. The Conservancy of Southwest Florida reports it has captured and ...
Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback