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Description: 编写了数据挖掘中的聚类和决策树结合使用的c++语言，实用性高
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Size: 76288 |
Author: jidannantong@126.com |
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Description: 用c++实现的决策树算法，windows环境下，希望对学习数据结构和算法的朋友有所帮助。-achieve with the Decision Tree Algorithm, windows environment, and I hope to learn from data structures and algorithms friends help.
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Size: 149504 |
Author: yu |
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Description: 数据挖掘分类算法决策树学习算法介绍以及SEE5的使用说明-data mining algorithms decision tree classification algorithm presentations and the use SEE5
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Size: 109568 |
Author: 黄瑞 |
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Description: matlab 决策树算法（包括id3.随机森林等算法，包括代码）
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Size: 290734 |
Author: syd@1111 |
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Description: 利用决策树训练训练器 分辨 有毒蘑菇和无毒蘑菇 java书写，包含训练集及说明 代码无bug(Using decision tree training trainer to distinguish poisonous mushroom and non-toxic mushroom Java writing, including training set and explanation code.)
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Size: 38912 |
Author: 西书城店
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Description: 决策树源文件，实例，内容详解，word文档(Decision tree source file, instance)
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Size: 6144 |
Author: 虫无
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Description: 决策树，源代码，注释和详解，内附加说明，id3，CD_4型决策树(Decision tree, source code, notes and detailed explanation,)
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Size: 24576 |
Author: 虫无
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Description: 决策树id3算法matlab代码，已调试，根据需要改写main函数，实现数据分类功能(code for decision tree)
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Size: 4096 |
Author: 辛巴达
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Description: 模式识别中决策树cart的实现 代码简单 比较好用(pattern recognition decision tree)
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Size: 2169856 |
Author: adf&683
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Description: 基础决策树算法适合初学者第一次尝试r编程(simple decision tree)
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Size: 7168 |
Author: Shirley&
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Description: 利用R语言实现决策树，使用 party 包构建决策树，使用 rpart 包构建决策树，以及随机森林的构建(using R language analyizing ...)
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Size: 205824 |
Author: spoilboy
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Description: 本代码基于MATLAB平台完成，对图像进行相应的决策树分类(This code is based on the MATLAB platform, for the corresponding decision tree classification)
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Size: 1024 |
Author: 嘻嘻sunshine
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Description: 数据处理中经常使用决策树算法，在MATLAB中编辑决策树算法(Decision tree algorithm is often used in data processing, and the decision tree algorithm is edited in MATLAB)
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Size: 2178048 |
Author: 逍遥之人
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Description: Java实现用ID3算法构建决策树(Java implementation using ID3 algorithm to build decision tree)
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Size: 13312 |
Author: 花泽大白菜 |
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Description: 决策树可对数据进行分类，选出最大增益属性。(Decision tree can be classified data, select the maximum gain attribute.)
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Size: 16384 |
Author: 格格啊 |
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Description: 给出对决策树与随机森林的认识。主要分析决策树的学习算法：信息增益和ID3、C4.5、CART树，然后给出随机森林。
决策树中，最重要的问题有3个:
1. 特征选择。即选择哪个特征作为某个节点的分类特征；
2. 特征值的选择。即选择好特征后怎么划分子树；
3. 决策树出现过拟合怎么办？
下面分别就以上问题对决策树给出解释。决策树往往是递归的选择最优特征，并根据该特征对训练数据进行分割。(The understanding of decision tree and random forest is given. This paper mainly analyzes the learning algorithm of decision tree: information gain and ID3, C4.5, CART tree, and then give the random forest.
Among the decision trees, there are 3 of the most important issues.
1. feature selection. Which is to choose which feature as the classification of a node;
2. the selection of eigenvalues. That is, how to divide the subtrees after the selection of the good features.
3. how to do the fitting of the decision tree?
The following questions are explained on the decision tree respectively. The decision tree is often the optimal feature of the recursive selection, and the training data are segmented according to the feature.)
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Size: 2114560 |
Author: ZJN27 |
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Description: 决策树和决策森林的代码，很不错，适合初学者，一起交流一起进步(The decision tree and decision forest code, very good, suitable for beginners, together with the progress of communication)
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Size: 2113536 |
Author: 啊大苏打 |
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Description: 此处python实现机器学习的决策树算法(A decision tree algorithm for realizing machine learning in Python)
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Size: 6144 |
Author: didi1 |
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Description: 使用决策树进行R语言建模的例子，是模式表达领域的一个例子。(An example of R language modeling using decision tree algorithm)
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Size: 1024 |
Author: yyuan15 |
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Description: 人工智能AI，决策树和神经网络的原理说明(MEMORY-EFFICIENT GLOBAL REFINEMENT OF DECISION-TREE ENSEMBLES AND ITS APPLICATION TO FACE ALIGNMENT)
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Size: 450560 |
Author: CarefulYang |
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