Abstract
Linear classifiers are of great significance in the classification field. In this paper, with meticulous studies on the linear classifiers, we gained a general framework for constructing fast trained linear classifiers, and found the key point that dominated the performance of the classifiers. Based on that result, we brought forward a mutual information based (MI-B) linear classifier. Experiments showed that the new method achieved a striking performance improvement over all the existing fast trained linear classifiers and worked stably. In some dataset it even outperformed the linear support vector machine (LSVM)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: 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.
