A decision tree model that tries to cover all aspects of lending decision can become very unwieldy.
能够涵盖所有贷款决策的决策树很难实现，也不方便。
Now consider how a decision tree model can be built of the decision structure visualized in the influence diagram.
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？
Two algorithms for structuring decision tree model of multi-dimensional time series classification were presented.
并给出了两种构造多维时间序列分类的决策树模型算法。
The paper stresses on the technology and methods, such as AHP, blurry integrative assessment, matrix decision model, decision tree model, and nonconfirm decision model.
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。
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.
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。
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.
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。
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.
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。
This paper proposes a framework for decision tree construction algorithms that supports both model exchange and mobile communication churn analysis.
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。
An MSS spectral form correlation model and a histogram decision tree classifier are presented.
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。
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.
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。
In this paper, a robust and effective decision tree improved model R-C4.5 and its simplified version are introduced.
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, the information of construction land-use is extracted by the decision tree and mixed pixel decomposition 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。
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.
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。
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.
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。
Generally, model can be expressed by classification rule, decision tree and mathematical formula.
通常，模型可以用分类规则、判定树或数学公式表示。
This paper analyzes existing reputation models, proposes a P2P reputation model using trust mechanisms and recommendation mechanisms, and optimizes the model by the mentality of decision tree.
分析现有信誉模型，提出一种使用信任机制和推荐机制的P 2 P信誉模型，利用决策树思想优化该模型。
The paper establishes decision-making tree data mining model and clustering data mining model to make data mining with a multi-dimension data collection.
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。
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.
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。
Knowledge discovery component take SLIQ as basic arithmetic. It provides classification model in two stage forms which aim at training suit. That is decision tree and productive rule.
知识发现，采用SLIQ快速可伸缩算法，分类模型用判定树与产生式规则两种形式描述。
Then it completes the case researches below with data mining technologies:(1)With decision-tree algorithm , it creates a model which classifies the credit degrees of personal loan customers.
具体地，完成了如下实例研究：①利用判定树算法对信用度好的个人信贷客户进行归纳分类模型的建立。
Decision Tree Apply Model to Test Data Test Data Start from the root of...
分类阶段从根开始，按照决策树的分类属性逐层往下划分，直到叶节点，获得概念。
Decision Tree Apply Model to Test Data Test Data Start from the root of...
分类阶段从根开始，按照决策树的分类属性逐层往下划分，直到叶节点，获得概念。
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