How to infer the informational energy from small datasets

Angel Cafaron, Razvan Andonie
2012 2012 13th International Conference on Optimization of Electrical and Electronic Equipment (OPTIM)  
Motivated by the problems in machine learning, we introduce a novel non-parametric estimator of Onicescu's informational energy. Our method is based on the k-th nearest neighbor distances between the n sample points, where k is a fixed positive integer. For some standard distributions, we investigate the performance of the estimator for small datasets.
doi:10.1109/optim.2012.6231921 fatcat:6kiy52r52fhjxlxgptflc22jye