Interactive Inductive Learning System

被引：1

作者：

Birzniece, Ilze ^{[1
]}

机构：

[1] Riga Tech Univ, Dept Syst Theory & Design, LV-1658 Riga, Latvia

来源：

DATABASES AND INFORMATION SYSTEMS VI: SELECTED PAPERS FROM THE NINTH INTERNATIONAL BALTIC CONFERENCE (DB&IS 2010) | 2011年 / 224卷

关键词：

Inductive learning; interactive inductive learning; machine learning; human-computer interaction; course comparison;

D O I：

10.3233/978-1-60750-688-1-380

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Inductive learning system learns classification from training examples and uses induced rules for classifying new instances. If a decision cannot be inferred from system rule base, a default rule is usually applied. In the paper a new interactive approach is proposed where in uncertain conditions an interactive inductive learning system can ask for human decision and improve its knowledge base with the rule derived from this decision. Problems and solutions of incorporation of human-made decision into rule base and aspects of choosing between static and incremental learning algorithms are analyzed in context of the proposed approach. An interactive inductive learning system is proposed to assist in study course comparative analysis.

引用

页码：380 / 393

页数：14