crossentropy: Cross Entropy
In FNN: Fast Nearest Neighbor Search Algorithms and Applications
View source: R/KNN.information.measures.R
crossentropy R Documentation
Cross Entropy
Description
KNN Cross Entropy Estimators.
Usage
crossentropy(X, Y, k=10, algorithm=c("kd_tree", "cover_tree", "brute"))
Arguments
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.
Details
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)].
Value
a vector of length k for crossentropy estimates using 1:k nearest neighbors, respectively.
Author(s)
Shengqiao Li. To report any bugs or suggestions please email: lishengqiao@yahoo.com
References
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.
FNN documentation built on Sept. 22, 2024, 9:06 a.m.
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View source: R/KNN.information.measures.R
| crossentropy | R Documentation |
Cross Entropy
Description
KNN Cross Entropy Estimators.
Usage
crossentropy(X, Y, k=10, algorithm=c("kd_tree", "cover_tree", "brute"))
Arguments
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. |
Details
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)].
Value
a vector of length k for crossentropy estimates using 1:k nearest neighbors, respectively.
Author(s)
Shengqiao Li. To report any bugs or suggestions please email: lishengqiao@yahoo.com
References
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.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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