Date of Award
7-23-2001
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Computer Science
First Advisor
Dr. Qiuming Zhu
Abstract
Introduction: A classifier is a hyperplane that separates data into different categories or classes. A trainable classifier is a classifier that may make its performance better in response to information it receives and tasks it takes. Training is the process by which the parameters of a function are adjusted in response to categories or classes. A training procedure is a training algorithm that implements the training process.
Recommended Citation
Fan, Rong, "Support vector machines for classification." (2001). Student Work. 3524.
https://digitalcommons.unomaha.edu/studentwork/3524
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Comments
A Thesis Presented to the Department of Computer Science and the Faculty of the Graduate College University of Nebraska In Partial Fulfillment of the Requirements for the Degree Master of Science University of Nebraska at Omaha. Copyright 2001 Rong Fan