Abstract
There are various error functions for pattern classifiers. This paper analyzes the error functions such as MSE(mean-squared error), CE(crossentropy) error, AN(additive noise) in MSE, MLS(mean log square) error, and nCE(nth order extension of CE) error functions in a statistical perspective. Also, the analyses include CFM(classification figure of merit). The results of analyses provide considerable insights into the properties of different error functions.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.