Search Results for "association"

NBA-Machine-Learning-Sports-Betting is an open-source Python project that applies machine learning techniques to predict outcomes of National Basketball Association games for analytical and betting-related research. The system gathers historical team statistics and game data spanning multiple seasons, beginning with the 2007–2008 NBA season and continuing through the present. Using this dataset, the project constructs matchup features that represent team performance trends and contextual information about each game. ...

...The system processes detection results from 3D object detectors that analyze LiDAR point clouds and uses them to track multiple objects across consecutive frames. Its tracking pipeline relies on a combination of classical algorithms, including a Kalman filter for state estimation and the Hungarian algorithm for data association between detected objects and existing tracks. This relatively simple design allows the tracker to achieve very high processing speeds while maintaining competitive tracking accuracy. The project also introduces new evaluation metrics specifically designed for assessing performance in 3D tracking benchmarks. The framework has been evaluated on widely used datasets such as KITTI and nuScenes and demonstrates strong performance compared with more complex tracking systems.

yacaree: Yet Another Closure-based Association Rules Experimentation Environment (Development stalled here, check out under Wiki to find where it went.)

Ferda is a user friendly data mining tool. It is a modular distributed multiplatform framework based on Internet Communications Engine. Ferda is very powerful in working with association rules.

Wikipedia Concept Association Map (WCAM) is new approach for textual knowledge representation and understanding. All concepts and associations are stored in a graph database for better performance and easy distribution.