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

Abstract

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.