决策树归纳法ID3是人工智能机器学习中发展较快的一种归纳学习算法,而目前的ID3及其改进算法亦因各种问题限制了其在工程中的应用.基于决策树归纳学习算法示例学习最优化的理论,用在多概念学习条件下对多特征属性值进行分组聚类实现优化的方法,导出了定义在多概念空间上的决策树归纳学习算法MNID.这种新算法对工程技术领域普遍存在的多概念学习问题,有较好的应用价值 Decision tree inductive method ID3 is a kind of inductive learning algorithm developed rapidly in the machine learning of artificial intelligence, and the current ID3 and its improved algorithms also limit its application in engineering due to various problems.Examples based on the decision tree inductive learning algorithm Learning optimization theory, the method of clustering multi-attribute attribute value under the condition of multi-concept learning is used to realize optimization, and the decision tree inductive learning algorithm MNID which is defined in multi-concept space is derived. There are many multi-concept learning problems in the field, which have good application value