Term of Award
Summer 2004
Degree Name
Master of Computer Science
Document Type and Release Option
Thesis (restricted to Georgia Southern)
Department
Department of Computer Science
Committee Chair
Wen-Ran Zhang
Committee Member 1
Ardian Greca
Committee Member 2
Jian Ping Wang
Committee Member 3
Xiezhang Li
Abstract
The amount of data stored to gather information is growing at an amazing speed nowadays which leads to the difficulties of extracting knowledge from that data. The field of Data mining plays an important role in the extraction of implicit and actionable knowledge from extremely large datasets. It is a field that plays an important role in the world of fuzzy logic and neural networks as well.
This thesis describes and outlines the result of a study with raw data of a folding legged 3-linked uniped robot used to focus on the formal study of identifying agents that bear most information and their usefulness. This identification of bearing the most information is obtained by using Information Gain and Gini methods of data mining. The two methods were used so that a comparison could be made between them.
Copyright
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Recommended Citation
Sadekin, Rafique, "Agent Identification Using Information Gain and Gini Indexing Methods for Intelligent Control" (2004). Legacy ETDs. 1123.
https://digitalcommons.georgiasouthern.edu/etd_legacy/1123
