crossentropy {FNN} | R Documentation |
KNN Cross Entropy Estimators.
crossentropy(X, Y, k=10, algorithm=c("kd_tree", "cover_tree", "brute"))
X |
an input data matrix. |
Y |
an input data matrix. |
k |
the maximum number of nearest neighbors to search. The default value is set to 10. |
algorithm |
nearest neighbor search algorithm. |
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)]
.
a vector of length k
for crossentropy estimates using 1:k
nearest neighbors, respectively.
Shengqiao Li. To report any bugs or suggestions please email: lishengqiao@yahoo.com
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.