- 树形判定分类法
- decision: n. 1.决定。 2.判决。 3.决议。 4.决心；决断 ...
- tree: n. 1.树〔主要指乔木，也可指较大的灌木〕。 ★玫瑰可 ...
- classifier: n. 1.分类者。 2.【矿物】分级机。 3.【化学】 ...
- decision tree classifier: 决策树分类器; 树型判定分类程序; 树形判定分类程序; 树形判定分类法
- tree classifier: 树状分类器
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decision-tree classifier中文什么意思
- 树形判定分类法
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例句与用法
- Data warehouse is a hot research area in 90s its main motif is to provide the decision - maker a powerful tool : gathering the data in pure consistent , relevant pattern , and making use of the data in managing analyzing , data - mining purposec that means that the decision - maker can use the tool to understand , grasp the situation of the business from different directions and forecast the future of it when using data warehouse , the processing speed determines data warehouse ' s practicability and processing ability the hoc ( highway decision center ) system realized before solves some key problems about intermediate scale data , mainly concentrating data warehouse performance coefficient when using hdc in large scale data , it encountered processing speed problem then the settlement of this problem becomes a major research point so , based on the former research achievements , the present task is to construct the renowned data warehouse architecture and its relevant algorithms , then adapts the system to the large scale dataset with data mining functions c this paper is a part of the research in order to construct the powerful system , a key problem is to cope with the processing - speed problem and the data space problem , etc , - caused by the large scale dataset and magnificent dataset this is also the core in the present data mining research this paper ' s motive is to design and realize a decision - tree classifier in the data warehouse system for large - scale dataset
大型数据仓库的处理速度问题目前是制约其推广应用的关键所在，也是这一领域的一个重要研究课题，也正是我们当前工作的重点：在前期研究工作的基础上围绕提高大型数据仓库处理速度问题，建立改进的数据仓库系统模型和相关算法，开发出面向中级以上企事业单位的、具有数据挖掘和分析能力的大型数据仓库系统。建立大型数据仓库所面临的关键问题，是如何妥善解决实际业务数据的大规模、海量特征所带来的处理速度和空间等问题，这也是当前挖掘技术研究必然面对的核心问题。本研究的目的是设计并实现大型数据仓库系统中的分类数据挖掘工具? ?决策树分类器，主要工作是在综合了解现有决策树分类算法的研究情况的前提下，对决策树算法适应大规模数据集的问题进行探讨，力求设计出能较好地适应大规模数据的分类器算法。