| 摘要: |
| 为了支持在事实不完全或不充分环境中的有效推理，作者提出了一种归纳机器学习方法，并设计了一个规则向量投影算法，使用木文介绍的算法可对原始知识实行归纳，生成含一系列全新分类概念和推理路经的网络知识库，基于该知识库的机器推理系统，在作出诊断决策时所需事实量可大为减少，因此在信息量不足的情况下仍能具有很高的推理性能． |
| 关键词: 专家系统 机器学习 归纳学习 知识库 分类 |
| DOI： |
| 分类号: |
| 基金项目: |
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| RULE VECTOR PROJECTION ALGORITHM──AN INDUCTIVE MACHINE LEARNING METHOD |
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Li Shaocheng
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| Abstract: |
| To support the effective reasoning in the circumstances of incomplete andinsufficient facts, the author presented an inductive machine learning method, and designed a rule vector projection algorithm. With the method implemented by the algorithmthe primitive knowledge are processed by inductive approach, created a network knowledge base full of new classification concepts and paths for reasoning. Based on the knowledge base the quantity of facts needed in a diagnostic decision making by a machine inference system can sharply be reduced, thus a high performance can still be achieved by thesystem, despite of short information. |
| Key words: Expert system machine learning inductive learning knowledge base classification. |
