KNN Cross Entropy Estimators.
crossentropy(X, Y, k=10, algorithm=c("kd_tree", "cover_tree", "brute"))a vector of length k for crossentropy estimates using 1:k nearest neighbors, respectively.
an input data matrix.
an input data matrix.
the maximum number of nearest neighbors to search. The default value is set to 10.
nearest neighbor search algorithm.
Shengqiao Li. To report any bugs or suggestions please email: lishengqiao@yahoo.com
If p(x) and q(x) are two continuous probability density functions,
then the cross-entropy of p and q is defined as
\(H(p;q) = E_p[-\log q(x)]\).
S. Boltz, E. Debreuve and M. Barlaud (2007). “kNN-based high-dimensional Kullback-Leibler distance for tracking”. Image Analysis for Multimedia Interactive Services, 2007. WIAMIS '07. Eighth International Workshop on.