Improved Classification In Flat Networks

Author

Madhu Gannapal

Graduation Semester and Year

2010

Language

English

Document Type

Thesis

Degree Name

Master of Science in Electrical Engineering

Department

Electrical Engineering

First Advisor

Michael T Manry

Abstract

It is shown that optimal flat networks can be found as solutions to least squares problems. An algorithm is presented to improve existing classifier training methods by changing the desired outputs. The algorithm is based on minimum probability of error. The algorithm's performance is compared with those of other algorithms including the Bayes Gaussian classifier. The Convergence of training and the effects of outliers are analyzed in all the algorithms presented here.

Disciplines

Electrical and Computer Engineering | Engineering

License

This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.

Comments

Degree granted by The University of Texas at Arlington

Recommended Citation

Gannapal, Madhu, "Improved Classification In Flat Networks" (2010). Electrical Engineering Theses. 137.
https://mavmatrix.uta.edu/electricaleng_theses/137