A Multi-Tier Knowledge Discovery Info-Structure Using Ensemble Techniques [QA76.9.D35 S158 2007 f rb].

Fokus utama kami ialah untuk mempelajari keujudan peraturan-peraturan yang ditemui daripada data-data tanpa catatan serta menjana keputusan yang lebih tepat dan muktamad. Ini dilakukan melalui kaedah penghibridan yang merangkumi kedua-dua mekanisma berselia dan tidak berselia. Our terminal focu...

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Bibliographic Details
Main Author: Karthigasoo, Sakthiaseelan
Format: Thesis
Language:English
Published: 2007
Subjects:
QA76.75-76.765 Computer software
Online Access:http://eprints.usm.my/8668/
Abstract Abstract here
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author Karthigasoo, Sakthiaseelan
author_facet Karthigasoo, Sakthiaseelan
author_sort Karthigasoo, Sakthiaseelan
description Fokus utama kami ialah untuk mempelajari keujudan peraturan-peraturan yang ditemui daripada data-data tanpa catatan serta menjana keputusan yang lebih tepat dan muktamad. Ini dilakukan melalui kaedah penghibridan yang merangkumi kedua-dua mekanisma berselia dan tidak berselia. Our terminal focus is to learn rules instances that have been discovered from unannotated data and generate results with high accuracy. This is done via a hybridized methodology which features both supervised and unsupervised techniques. Unannotated data without prior classification information could now be useful as our research has brought new insight to knowledge discovery and learning altogether.
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spelling usm-86682017-04-14T12:18:37Z http://eprints.usm.my/8668/ A Multi-Tier Knowledge Discovery Info-Structure Using Ensemble Techniques [QA76.9.D35 S158 2007 f rb]. Karthigasoo, Sakthiaseelan QA76.75-76.765 Computer software Fokus utama kami ialah untuk mempelajari keujudan peraturan-peraturan yang ditemui daripada data-data tanpa catatan serta menjana keputusan yang lebih tepat dan muktamad. Ini dilakukan melalui kaedah penghibridan yang merangkumi kedua-dua mekanisma berselia dan tidak berselia. Our terminal focus is to learn rules instances that have been discovered from unannotated data and generate results with high accuracy. This is done via a hybridized methodology which features both supervised and unsupervised techniques. Unannotated data without prior classification information could now be useful as our research has brought new insight to knowledge discovery and learning altogether. 2007 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/8668/1/A_MULTI-TIER_KNOWLEDGE.pdf Karthigasoo, Sakthiaseelan (2007) A Multi-Tier Knowledge Discovery Info-Structure Using Ensemble Techniques [QA76.9.D35 S158 2007 f rb]. Masters thesis, Universiti Sains Malaysia..
spellingShingle QA76.75-76.765 Computer software
Karthigasoo, Sakthiaseelan
A Multi-Tier Knowledge Discovery Info-Structure Using Ensemble Techniques [QA76.9.D35 S158 2007 f rb].
thesis_level Master
title A Multi-Tier Knowledge Discovery Info-Structure Using Ensemble Techniques [QA76.9.D35 S158 2007 f rb].
title_full A Multi-Tier Knowledge Discovery Info-Structure Using Ensemble Techniques [QA76.9.D35 S158 2007 f rb].
title_fullStr A Multi-Tier Knowledge Discovery Info-Structure Using Ensemble Techniques [QA76.9.D35 S158 2007 f rb].
title_full_unstemmed A Multi-Tier Knowledge Discovery Info-Structure Using Ensemble Techniques [QA76.9.D35 S158 2007 f rb].
title_short A Multi-Tier Knowledge Discovery Info-Structure Using Ensemble Techniques [QA76.9.D35 S158 2007 f rb].
title_sort multi tier knowledge discovery info structure using ensemble techniques qa76 9 d35 s158 2007 f rb
topic QA76.75-76.765 Computer software
url http://eprints.usm.my/8668/
work_keys_str_mv AT karthigasoosakthiaseelan amultitierknowledgediscoveryinfostructureusingensembletechniquesqa769d35s1582007frb
AT karthigasoosakthiaseelan multitierknowledgediscoveryinfostructureusingensembletechniquesqa769d35s1582007frb

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