1、

The end mark reduces the difference caused by the difference of phone number, and the complexity of building the decision tree for the word transition variable and the cost of reading the parameters when training and decoding are reduced accordingly.

词结束标记的设定减少了词中音子个数的差别所引起的差异性,降低了构建决策树的复杂度,训练和识别时参数读取的时间也相应减少。

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2、

Decision Tree Based on ASTER Image Classification and Its Application

基于ASTER数据遥感影像的决策树分类

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3、

A Study on Credit Risk Assessment Method Based on Decision Tree

基于决策树的信用风险评估方法研究

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4、

Decision Tree Classification Method Based on Correlation Between Attributes

一种基于关联性度量的决策树分类方法

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5、

Study on Data Stream Mining Algorithm Based on Decision Tree

基于决策树的数据流挖掘算法的研究

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6、

Thirdly, the misuse detection model based on decision tree is proposed.

提出了一个基于决策树的误用检测模型。

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7、

Application of Bayesian decision tree to recognition of English present participle

贝叶斯决策树在英文现在分词词性识别中的应用

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8、

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。

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9、

Then this paper points out the defect of traditional financial warning methods and designs a united data mining system consisting of Logistic regression, associative rules, decision tree and neural network.

针对这些局限性,设计了由Logistic回归分析方法、关联规则、决策树和神经网络组成的联合数据挖掘系统。

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10、

Research on the Application of Decision Tree Data Mining Technology to the Performance Evaluation in Public Business Administration

决策树数据挖掘技术在公共事业管理绩效评价中的应用研究

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11、

Proposes a face recognition method which combines independent component analysis ( ICA), fuzzy support vector machine ( FSVM) and triple decision tree.

将独立成分分析(ICA)、模糊支持向量机(FSVM)以及三叉决策树相结合并应用于人脸识别。

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12、

Firstly this paper introduces several classification methods such as the Support Vector Method, Decision Tree and Naive Bayes Theory, and proposed using Support Vector Method ( SVM) to classify the face expression.

表情分类器训练,本文首先介绍了支持向量法、最近邻法、决策树、朴素贝叶斯等几种分类方法的分类原理,并提出了利用支持向量(SVM)的方法对人脸表情进行分类。

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13、

With Gradient Boosting Decision Tree model, adding the user behavior features including the title features, query features, click features to the literal features make accuracy increased by about 25%, recall rate increased by about 24% and F value increased by about 30%.

在梯度下降决策树模型中,加入标题、查询、点击等用户行为特征比单独使用字面特征准确率提高了约25%,召回率提高了约24%,F值提高了约30%。

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14、

Using computer modeling, researchers constructed a decision tree by using published data.

通过电脑建模,研究人员根据报道的数据建立了一个决策流程图。

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15、

With the decision tree, we can get the potential clients 'permission maximally to digging the clients' consumed potential.

运用决策树技术能最大限度地获得潜在客户的许可响应,挖掘客户的消费潜力。

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16、

The results are good, contrast to other methods the class regulation from decision tree is intuitionistic, easily understanding, quickly building.

结果证明该方式分类机能良好,与其他方式比拟,由决议计划树发现的分类规则表达方式直观,便于理解,生成速度也较快。

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17、

Uses the improvement the decision tree algorithm excavation forecast latent client base, and has given the gain latent customer reasonable feasible data mining flow.

采取改入的决议计划树算法挖掘预测潜伏客户群,并给出了获取潜伏客户的合理可行的数据挖掘流程。

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18、

Decision tree algorithm is one of the most widely studied and applied subjects, so research on the decision tree algorithm has high theoretic meaning and realistic value.

其中决议计划树分类算法是数据挖掘中最为普遍研讨和应用的一个课题,所以决议计划树分类算法的研讨具有很高的理论意义和应用价值。

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19、

To improve the shortcomings of web-based learning system, a new model of the personalized learning system is presented based on data mining, and how to use the decision tree and the BP-neural network to design the personalized navigation module detailedly are described.

为改善基于Web学习系统存在的不足,提出了一个基于数据挖掘技术的个性化学习系统模型,并详细描述了应用决策树及BP神经网络算法对个性化导航模块设计的方法。

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20、

Use Decision Tree Technology to Explore Gender Differences in Mobile Learning

决策树技术在移动学习性别差异研究中的应用

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