搜索资源列表
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决策树C45，用matlab编写的，数据挖掘算法。,Decision Tree C45, prepared by matlab, data mining algorithms.
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his algorithm was proposed by Quinlan (1993). The C4.5 algorithm generates a classification-decision tree for the given data-set by recursive partitioning of data. The decision is grown using Depth-first strategy. The algorithm considers all the poss
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为了准确地对监控场景中的运动目标进行语义上的分类，提出了一种基于聚类的核主成分分析梯度方向直方图和二又决策树支持向量机的运动目标分类算法。-In order to accurately monitor the movement of scene targets semantic classification, the clustering based on kernel principal component analysis of gradient direction histograms,
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实现ID3算法，在结果中以树表示出来。决策树是对数据进行分类，以此达到预测的目的。该决策树方法先根据训练集数据形成决策树，如果该树不能对所有对象给出正确的分类，那么选择一些例外加入到训练集数据中，重复该过程一直到形成正确的决策集。-ID3 algorithm to achieve, in the results that come out to the tree. Decision tree is to classify the data, thus achieving the purpose
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这是一个分类和回归树算法，它提供一种通用框架将各种各样不同的判定树实例化。-This is a classification and regression tree algorithm, which provides a common framework a wide variety of different decision tree instantiation.
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决策树算法的matlab实现，主要适用的是id3
算法思想-Decision Tree Algorithm to achieve the matlab main id3 algorithm is applicable to thinking
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c4.5 关于决策树decision tree的matlab实现程序 -c4.5 decision tree decision tree on the realization of the matlab program
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The matlab code implements the ensemble of decision tree classifiers proposed in: "L. Nanni and A. Lumini, Input Decimated Ensemble based on Neighborhood Preserving Embedding for spectrogram classification, Expert Systems With Applications doi:10.101
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决策树算法的CART算法，用MATLAB编写，能有，不错的。-CART decision tree algorithm algorithm, using MATLAB to prepare, to have, good.
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在matlab中实现ID3决策树算法--matlab源码-In the ID3 decision tree algorithm implemented in matlab- matlab source
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decision tree in matlab code
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this package is binary Decision Tree code implement in matlab.
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matlab中cart决策树源代码，用于数据的分类和预测。-source code in matlab cart decision tree for data classification and prediction.
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原为某课大作业，改进的决策树函数，使用matlab对ID3决策树算法进行了重现。支持树的建立，打印和使用。附带部分注解-A rewrite of decision tree in matlab.
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决 策 树 模 型决策树(Decision Tree)是在已知各种情况发生概率的基础上，通过构成决策树来求取净现值的期望值大于等于零的概率，评价项目风险，判断其可行性的决策分析方法，是直观运用概率分析的一种图解法。(The decision tree (Decision Tree) is the basis of probability in the known situations, through the form of decision tree to calculate
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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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本程序论述在MATLAB环境下如何实现神经网络，包括了常用的神经网络及相关理论，如BP神经 网络、RBF神经网络、SVM、SOM神经网络、灰色神经网络、决策树、随机森林、小波神经网络、NARX神经网络等以及各种优化算法与神经网络的结合。(This procedure describes how to realize neural network in MATLAB environment, including the commonly used neural network and relate
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基于matlab的机器学习中决策树算法，代码很完整，都能运行(Matlab-based decision tree algorithm in machine learning, the code is complete, can run)
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决策树分类小程序，分类一个酒的类别数据集，数据集里有三类酒，利用matlab自带的决策树函数，根据数据集进行建模，预测。决策树小程序Demo(Decision tree classification program, classification of a wine category data set, there are three types of wine in the data set, using the decision tree function of matlab, accord
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