至今已经提出了决策树的很多算法,通过分析已知的分类信息得到一个预测模型。
So far, there are many algorithms have been given and we can gain a prediction model by analyzed known catalog information.
实验方法是分析决策树算法中的多值偏向问题的传统方法,其缺点是需要具备该数据领域的专家知识。
Experiment is the traditional method for analysing multivalue BIOS of decision tree algorithm, but it has a fault that we must have the expertise of the specific field.
多值偏向是决策树算法中普遍存在的问题,以往人们对于多值偏向问题的分析主要是基于实验观测的。
Variety bias exists in many decision tree algorithms, and in the past people analyzed this problem mainly based on experiments.
基于上述分析,提出了决策树优化算法。
Based on the above analysis, a new algorithm of decision tree induction is proposed.
通过二叉决策树来分析车辆的压线过程,提高了车流量检测的可靠性;
Binary decision tree is used to analyze pressing line of vehicles to improve the reliability of the system.
本文比较和分析了几种典型的决策树算法,着重对ID 3算法和C4。
This thesis compares and analyzes the typical decision tree algorithms, the ID3 algorithm and C4.
另一方面,本文还利用决策树算法,对影响学生就业的因素进行了分析,得到了一些有价值的模式。
And on other hand, the thesis also analyzes the factors that affect the jobs of graduated student by adopting decision tree algorithm, and some valuable models are achieved.
该文提出了支持挖掘模型交换和移动通信客户流失分析的决策树算法框架。
This paper proposes a framework for decision tree construction algorithms that supports both model exchange and mobile communication churn analysis.
并具体分析比较了多种的典型聚类和决策树数据挖掘算法。
Some classical clustering algorithms and decision trees algorithms are analyzed and compared.
另外,本文在相关章节对形式概念分析和聚类分析进行比较以及分析总结了基于概念格的分类和决策树分类法的异同。
Moreover, this thesis compares FCA with clustering analysis, and analyzes the similarities and differences of classification based on concept lattice and decision tree.
不确定性决策方法包括肯定当量法、风险调整贴现率法、敏感性分析法和决策树法。
Uncertain decision approaches consist certainty equivalent approach, risk adjusted discount rate approach, sensitivity analysis and decision tree analysis.
对某大型液体火箭发动机的热试车数据及通过发动机模型仿真得到的故障数据进行动态时间弯曲分析,得到弯曲路径集,然后结合决策树方法进行了故障检测和诊断。
Through dynamic time warping analysis to the hot-fire test data and simulated fault data of a certain liquid rocket engine, the warped path sets were obtained.
本文重点介绍了两种基于并行算法的分类决策树的构造算法,并对它们的适用性及特点作了分析。
This paper introduces two construction algorithms of Classification decision tree based on parallel algorithm, and analyzes applicability.
其次,在解决工艺参数优化的问题中,本文提出了一种正演的方法,即结合使用决策树分类器以及人工神经网络进行综合分析的方法来完成。
Secondly, in solving the problem that the craft parameter is optimized, this paper has put forward a method to perform, which using decision tree and ANN carry on comprehensive.
在财务因素分析上,采用基于归纳推理方法的决策树方法,分析了财务因素对贷款风险分类的影响。
When analyze financial factor, decision tree method on the basis of inductive reasoning means is adopted to analyze the infection of financial factor to loan risk classification.
同时详细的阐述了决策树分类算法,并对比较流行的决策树算法id3、C4.5等算法进行详细分析与比较。
Meanwhile it describes the decision tree classification algorithm in detail, analyzes the ID3, C4.5 and other prevalent decision tree algorithm.
然后基于关联分析,提出了灰色决策树的模型,并给出了其决策的详细步骤。
Then based on relationship analysis, the gray decision-making tree method is proposed, and its decision-making steps are presented in detail.
筛选不同方面的因素,经过数据分析,得到决策树。
Choose factors from different aspect, analyze data, get decision trees.
通过对决策树算法的深入分析,我们围绕着C4.5决策树生成算法建立了一个分类预测系统并实现了与劳动力市场信息管理系统(LMIS)的集成。
With the thorough analysis on the algorithm of decision tree induction, we established a classification and prediction system based on C4.5 and accomplished the integration with the LMIS system.
最后进行了分步决策树分类实验和与传统分类方法的精度对比分析。
In the end, decision tree classification experiments results and contrastive precision accuracy are obtained.
随后,着重分析了决策树算法的理论背景以及实现步骤,并给出了C4.5算法的伪码实现。
Then, the paper emphasizes the theory and method of Decision Tree algorithm and realizes C4. 5 algorithm.
并按照ID 3算法建立了决策树数据挖掘模型的例子,用于分析评估客户资信。
A decision tree by using for ID3 algorithm has been established, which evaluates the customer's credit.
通过应用实例比较分析,证明该算法能生成最小化决策树,并且决策树生成规则切合实际。
The comparable and analyzable experiment shows that this algorithm can make a minimize decision tree whose rules are true.
本文主要是研究数据挖掘中的决策树算法以及决策树算法在具体的小灵通流失分析中的研究与分析。
This essay is researching the Decision Tree Algorithm of Data Mining and the use in the Customer Drain analysis.
本文介绍了数据挖掘的基本概念,重点分析了决策树C5算法。
This paper illustrates the basic concepts of data mining and in detail discusses the Algorithm C5 approach for data mining.
压缩视频镜头的分割是视频内容分析中的一个难点,由于镜头在组织和索引视频中起关键性的作用,提出了一种基于决策树的MPEG视频镜头分割算法。
Video shot detection is very crucial for content-based video analysis. Considering the importance of video shots, we propose a MPEG video shot detection based on decision tree.
介绍了垃圾邮件过滤技术,对决策树算法的基本思想进行阐述,分析比较其优点和不足,给出了基于ID5R算法的垃圾邮件过滤模型。
The merits and weak points of each algorithm are analyzed and compared, and a spam filtering model based on ID5R algorithm is presented.
粗糙集和决策树是知识挖掘和学习的重要方法,通常用来分析数据和形成预测模型。
Rough Set and Decision Tree, usually used to analyze the data and the formation of predictive models, are important methods of knowledge discovery and learning.
粗糙集和决策树是知识挖掘和学习的重要方法,通常用来分析数据和形成预测模型。
Rough Set and Decision Tree, usually used to analyze the data and the formation of predictive models, are important methods of knowledge discovery and learning.
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