{"id":{"repo_id":"gsu","oai_identifier":"oai:digitalcommons.georgiasouthern.edu:etd_legacy-1693"},"canonical_url":"https://search.dev.ndltd.org/etd/gsu/oai:digitalcommons.georgiasouthern.edu:etd_legacy-1693","repository":{"repo_id":"gsu","name":"Georgia Southern University","base_url":"https://digitalcommons.georgiasouthern.edu/do/oai/"},"display":{"title":"Agent Identification Using Information Gain and Gini Indexing Methods for Intelligent Control","abstract":"<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>","abstract_html":"&lt;p&gt;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.&lt;/p&gt; &lt;p&gt;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.&lt;/p&gt;","abstract_has_math":false,"creators":["Sadekin, Rafique"],"institution":null,"degree_name":"Master of Computer Science","degree_level":"Thesis (restricted to Georgia Southern)","degree_discipline":"Department of Computer Science","degree_department":null,"school":null,"contributors":["Ardian Greca","Jian Ping Wang","Xiezhang Li"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2004,"date_issued":"2004-01-01T08:00:00Z","date_published":"2004-01-01T08:00:00Z","updated_at":"2026-07-24T02:28:33Z","subjects":["ETD","Data storage","Datamining","Fuzzy logic","Neural networks","Gain method","Gini method","Computer Engineering","Computer Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.georgiasouthern.edu/etd_legacy/1123","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Ardian Greca","Jian Ping Wang","Xiezhang Li"]},{"key":"dc:creator","label":"Author","values":["Sadekin, Rafique"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2015-08-18T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Department of Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis (restricted to Georgia Southern)"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Computer Science"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["ETD","Data storage","Datamining","Fuzzy logic","Neural networks","Gain method","Gini method","Computer Engineering","Computer Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.georgiasouthern.edu/etd_legacy/1123"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["<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>"]},{"key":"dc:title","label":"Title","values":["Agent Identification Using Information Gain and Gini Indexing Methods for Intelligent Control"]}]}],"canonical_facts":{"dc:contributor":["Ardian Greca","Jian Ping Wang","Xiezhang Li"],"dc:creator":["Sadekin, Rafique"],"dc:date.available":["2015-08-18T07:00:00Z"],"dc:description.abstract":["<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>"],"dc:identifier":["https://digitalcommons.georgiasouthern.edu/etd_legacy/1123"],"dc:subject":["ETD","Data storage","Datamining","Fuzzy logic","Neural networks","Gain method","Gini method","Computer Engineering","Computer Sciences"],"dc:title":["Agent Identification Using Information Gain and Gini Indexing Methods for Intelligent Control"],"thesis:degree_discipline":["Department of Computer Science"],"thesis:degree_level":["Thesis (restricted to Georgia Southern)"],"thesis:degree_name":["Master of Computer Science"]},"updated_at":"2026-07-24T02:28:33Z"}