Search - data mining decision tree

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[Other resource] C4.5算法 DL : 1: 数据挖掘中的决策树C4.5算法的实现,用matlab实现-Data Mining Decision Tree Algorithm of C4.5, using Matlab to achieve
Update : 2008-10-13 Size : 2.25kb Publisher : 利军
[Other] DeTree DL : 0: 数据挖掘的决策树算法，C语言实现，可直接运行。-Data Mining Decision Tree Algorithm, C language and can run.
Update : 2008-10-13 Size : 7.45kb Publisher : 杨一
[Other resource] CART DL : 0: 用matlab编写的CART数据挖掘决策树算法-using Matlab CART prepared by the Data Mining Decision Tree Algorithm
Update : 2008-10-13 Size : 1.78kb Publisher : g
[Mathimatics-Numerical algorithms] VBDMDecisionTrees DL : 0: 一个关于数据挖掘的决策树算法-a data mining on the Decision Tree Algorithm
Update : 2025-02-17 Size : 100kb Publisher : 苟良
[Internet-Network] dminid DL : 0: 入侵检测中的数据挖掘方法研究.pdf-A Research into Data Mining Technology in Intrusion Detection. file type pdf
Update : 2025-02-17 Size : 599kb Publisher : 赵艳
[AI-NN-PR] ID3算法的源代码(vc) DL : 0: 数据挖掘中ID3分类算法的vc实现的源代码-Data Mining ID3 classification algorithm to achieve the vc source code
Update : 2025-02-17 Size : 52kb Publisher : 张乐
[AI-NN-PR] CART DL : 0: 用matlab编写的CART数据挖掘决策树算法-using Matlab CART prepared by the Data Mining Decision Tree Algorithm
Update : 2025-02-17 Size : 2kb Publisher : g
[matlab] C4.5算法 DL : 1: 数据挖掘中的决策树C4.5算法的实现,用matlab实现-Data Mining Decision Tree Algorithm of C4.5, using Matlab to achieve
Update : 2025-02-17 Size : 2kb Publisher : 利军
[AI-NN-PR] projet DL : 0: 一个模拟weka的系统，输入文件格式和weka的一样，实现决策树的分析以及通过数据挖掘整理规则集合，很值得新手学习-a simulation system, the importation of files and weka, the same realization of the decision tree analysis and data mining collated by the rules set, is worth learning newcomers
Update : 2025-02-17 Size : 37kb Publisher : 郑磊
[Other] DeTree DL : 0: 数据挖掘的决策树算法，C语言实现，可直接运行。-Data Mining Decision Tree Algorithm, C language and can run.
Update : 2025-02-17 Size : 7kb Publisher : 杨一
[Bio-Recognize] C4.5_Kidney DL : 0: 以从医院病案室获得的3022例数据为样本，在完成样本数据库以及糖尿病并发症的多维数据集设计后，以糖尿病并发症流行病学知识发现为重点，研究定性数据定量化挖掘模型及算法引擎的设计与实现，即将关联模型引入糖尿病并发症的流行病学研究.运用决策树技术对数据样本进行分析，采用C4.5找到最优决策树-cases from the hospital to obtain the data for 3,022 cases samples the completion of the sample database and diabetic complications multidimensional data sets design, Complications of diabetes epidemiology knowledge discovery as the focus, Quantitative study of qualitative data mining engine model and algorithm design and implementation, Relational Model forthcoming introduction of diabetic complications epidemiological studies. the use of decision tree technical data samples for further analysis. C4.5 used to find optimal decision tree
Update : 2025-02-17 Size : 301kb Publisher : Eric Cheng
[AI-NN-PR] decision-making-tree-algorithm DL : 0: One kind of decision-making tree algorithm, can be seen as one kind data mining algorithm ,find the rule from large-scale data middle.
Update : 2025-02-17 Size : 15kb Publisher : 渐令
[Other] id3 DL : 0: Decision Tree 决策树算法ID3 数据挖掘分类-ID3 Decision Tree Algorithm Decision Tree Data Mining Category
Update : 2025-02-17 Size : 111kb Publisher : chen
[matlab] tree DL : 0: 数据挖掘里的判定树算法，用matlab编写。-Data Mining in the decision tree algorithm, using matlab prepared.
Update : 2025-02-17 Size : 13kb Publisher : 烈马
[AI-NN-PR] jieceshu DL : 0: 有关人工智能，数据挖掘中的决策树算法的实现包括相关的测试数据-On artificial intelligence, data mining, decision tree algorithm in the implementation, including relevant test data
Update : 2025-02-17 Size : 3.52mb Publisher : 常
[Documents] paper DL : 0: 关于数据挖掘的分类算法，主要介绍基于不确定数据的决策树算法-With regard to the classification of data mining algorithms, mainly introduces the decision tree algorithm based on uncertain data
Update : 2025-02-17 Size : 669kb Publisher : 任广明
[JSP/Java] DecisionTree DL : 0: A java based open source data mining code for decision tree algorithm
Update : 2025-02-17 Size : 8kb Publisher : Shiplu
[Windows Develop] AttacksClassificationinAdaptivIntrusion DL : 0: Recently, information security has become a key issue in information technology as the number of computer security breaches are exposed to an increasing number of security threats. A variety of intrusion detection systems (IDS) have been employed for protecting computers and networks from malicious network-based or host-based attacks by using traditional statistical methods to new data mining approaches in last decades. However, today s commercially available intrusion detection systems are signature-based that are not capable of detecting unknown attacks. In this paper, we present a new learning algorithm for anomaly based network intrusion detection system using decision tree algorithm that distinguishes attacks from normal behaviors and identifies different types of intrusions. Experimental results on the KDD99 benchmark network intrusion detection dataset demonstrate that the proposed learning algorithm achieved 98 detection rate (DR) in comparison with other existing methods.-Recently, information security has become a key issue in information technology as the number of computer security breaches are exposed to an increasing number of security threats. A variety of intrusion detection systems (IDS) have been employed for protecting computers and networks from malicious network-based or host-based attacks by using traditional statistical methods to new data mining approaches in last decades. However, today s commercially available intrusion detection systems are signature-based that are not capable of detecting unknown attacks. In this paper, we present a new learning algorithm for anomaly based network intrusion detection system using decision tree algorithm that distinguishes attacks from normal behaviors and identifies different types of intrusions. Experimental results on the KDD99 benchmark network intrusion detection dataset demonstrate that the proposed learning algorithm achieved 98 detection rate (DR) in comparison with other existing methods.
Update : 2025-02-17 Size : 305kb Publisher : keerthi
[Mathimatics-Numerical algorithms] tree DL : 0: 数据挖掘-决策树-c4.5算法的java代码实现-Data Mining- Decision Tree algorithm java code-c4.5
Update : 2025-02-17 Size : 907kb Publisher : 王倩
[Books] Learning Data Mining with Python DL : 0: Python数据挖掘入门与实践本书作为数据挖掘入门读物，介绍了数据挖掘的基础知识、基本工具和实践方法，通过循序渐进地讲解算法，带你轻松踏上数据挖掘之旅。本书采用理论与实践相结合的方式，呈现了如何使用决策树和随机森林算法预测美国职业篮球联赛比赛结果，如何使用亲和性分析方法推荐电影，如何使用朴素贝叶斯算法进行社会媒体挖掘，等等。本书也涉及神经网络、深度学习、大数据处理等内容。本书面向愿意学习和尝试数据挖掘的程序员。(Introduction and practice of Python data mining As a primer on data mining, this book introduces the basic knowledge, basic tools and practical methods of data mining. By step-by-step explanation of the algorithm, you can easily embark on the journey of data mining. This book uses a combination of theory and practice, showing how to use the decision tree and random forest algorithm to predict the results of the American professional basketball league game, how to use the affinity analysis method to recommend movies, how to use the naive Bayesian algorithm for social media mining ,and many more. This book also covers neural networks, deep learning, big data processing and more. This book is for programmers who are willing to learn and experiment with data mining.)
Update : 2025-02-17 Size : 3.72mb Publisher : ycg95

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