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How to infer the informational energy from small datasets
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