Agent Identification Using Information Gain and Gini Indexing Methods for Intelligent Control

<p>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.</p> <p>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.</p>

Name thesis:degree_name

Master of Computer Science

Level thesis:degree_level

Thesis (restricted to Georgia Southern)

Discipline thesis:degree_discipline

Department of Computer Science

Year dc:date.available

2004

Author dc:creator

• Sadekin, Rafique

Contributors dc:contributor

• Ardian Greca
• Jian Ping Wang
• Xiezhang Li

• ETD
• Data storage
• Datamining
• Fuzzy logic
• Neural networks
• Gain method
• Gini method
• Computer Engineering
• Computer Sciences

Repository record dc:identifier

https://digitalcommons.georgiasouthern.edu/etd_legacy/1123

OAI identifier oai:identifier

oai:digitalcommons.georgiasouthern.edu:etd_legacy-1693