并给出了两种构造多维时间序列分类的决策树模型算法。
Two algorithms for structuring decision tree model of multi-dimensional time series classification were presented.
那么决策树模型又是如何根据可视化影响图网中的结构逐渐形成的呢？
Now consider how a decision tree model can be built of the decision structure visualized in the influence diagram.
检验结果表明，该模型在预测精度、实用价值和鲁棒性方面都优于传统的统计模型、神经网络模型和决策树模型。
Empirical results show that genetic programming model is more advantageous than traditional statistical models, neural network models and decision tree models in prediction accuracy and robustness.
针对英文现在分词词性标注这一特定问题存在的难点分析了隐马尔可夫模型(HMM)的不足，提出了贝叶斯决策树模型。
Concerning the difficulties in part-of-speech tagging in English present participle, the authors analyzed the drawbacks of Hidden Markov Models (HMM) and proposed Bayesian decision tree model.
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.
决策树是分类中常用的模型之一，自1966年被提出以来已经得到了广泛的研究和应用。
Decision tree is one of the models that are often used in classification, and it has been widely researched and applied since it was proposed in 1966.
实验结果表明，应用GP决策树算法能够正确完成对趋势预测模型的选择。
Experimental results show that the choice for trend forecasting models can be correctly finished by using GP-decision tree algorithm.
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.
本文提出MSS数据波谱形态相关模型和直方图决策树分类法。
An MSS spectral form correlation model and a histogram decision tree classifier are presented.
论文提出了一种健壮有效的决策树改进模型R - C4.5及其简化版本。
In this paper, a robust and effective decision tree improved model R-C4.5 and its simplified version are introduced.
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.
决策树是归纳学习和数据挖掘的重要方法，通常用来形成分类器和预测模型。
Decision tree is an important method in induction learning as well as in data mining, which can be used to form classification and predictive model.
采用决策树和混合像元分解模型进行建设用地信息提取。
In this paper, the information of construction land-use is extracted by the decision tree and mixed pixel decomposition model.
实验结果表明，系统所使用的轮廓线向量图像特征也能够较有效地应用于图像方向分类，而机器学习则能够有效地为之建立决策树分类模型。
Using teacher images and machine learning method, an image direction classification model is built as a decision tree. Test results argued the validity of this method.
目的利用居民健康档案数据和决策树方法，建立糖尿病预测模型，建立社区新型糖尿病高危人群筛选模式。
OBJECTIVE To set up the prediction model for evaluating the risk of diabetes mellitus(DM)in community by application of decision tree with data from health records.
建立了渔船决策树挖掘模型及渔船年审聚集挖掘模型，对多维数据集进行了数据挖掘。
The paper establishes decision-making tree data mining model and clustering data mining model to make data mining with a multi-dimension data collection.
该文介绍了随机决策树分类模型及如何启发式选择随机决策树的深度及棵树，通过实验证明了该算法的有效性和高效性。
This paper introduces the classification model of random decision tree and how to heuristic selected the depth and the number, the experiment shows that the algorithm is effectiveness and efficiency.
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.
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.
在结合数据融合和数据挖掘的医疗监护模型的建模方面，采用多层感知器网络和决策树方法建立报警决策器的模型。
For modeling of medical ward based on data fusion and data mining, multi - layer perceptron network and decision trees are used.
本文利用不确定推理中的概率推理方法，设计了购买决策树回溯推理的模型和算法，有效解决了这一问题。
Using uncertain reasoning, a reasoning model and an algorithm are presented, which give the answer to this problem effectively.
在决策树理论的指导下，通过信息增益的应用和公式的构造获取属性重要程度评价值，结合决策树挖掘得到个人住房贷款风险评估模型。
Based on the theories of decision tree, this paper gets the importance assessment value among attributes through applying information gain and constructing formula.
本文采用C4.5决策树算法构建空气质量评价系统，挖掘空气污染物和空气等级关系的历史数据，建立空气污染物-空气等级智能评价模型。
Intelligent evaluation model for air quality based on C4.5 decision tree algorithm is established through the historical data of air pollutants and air quality classes in this article.
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.
实验表明，R-C 4.5决策树在保持模型预测准确率的同时，有效改进了树的健壮性。
The results of experiments show that R-C 4.5 improves the predictive accuracy and robustness.
其中重点探讨了定性与定量相结合的层次分析AHP法、模糊综合评判方法、矩阵决策模型方法、决策树决策模型方法、不确定性决策模型方法等。
The paper stresses on the technology and methods, such as AHP, blurry integrative assessment, matrix decision model, decision tree model, and nonconfirm decision model.
该模型通过对使用多个样本集分别训练出的多棵决策树预测函数进行逻辑回归来得到最终的预测函数。
In this model, a logistic regression function is induced from multiple decision trees, which are built based on different training sample sets respectively.
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.
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.
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