Title :
An upper bound estimate on classification error (Corresp.)
fDate :
9/1/1968 12:00:00 AM
Abstract :
An upper bound estimate on the Bayes misclassification error is derived using a kernel function to estimate probability density functions. As a result of this bound, a relationship between a Euclidean distance and a probability of misclassification is indicated.
Keywords :
Bayes procedures; Pattern classification; Density functional theory; Euclidean distance; Extraterrestrial measurements; Kernel; Mathematical model; Measurement units; Probability; Random variables; Sufficient conditions; Upper bound;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.1968.1054198
