详细说明:这个一些经典的数据挖掘matlab源程序,比较全。-some of the classic source Matlab data mining, comparative whole.
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经典的数据挖掘程序 matlab 数据挖掘 数据挖掘matlab c4.5 matlab code 数据挖掘源程序 数据挖掘 matlab C4.5 matlab code SLIQ算法 源代码 数据挖掘程序 ada_boost.m 数据挖掘 MDS "MATLAB" matlab 数据挖掘 程序 数据挖掘程序下载 数据挖掘 matlab ID3 and C4.5 matlab code
[Arnold.rar] - 本程序用Matlab语言实现了基于Arnold变换的图像置乱算法
[数据挖掘中CART算法实现.rar] - 数据挖掘中CART算法实现(用MATLAB实现)
[visa.rar] - 一个简单的数据挖掘程序,有贝叶斯方法和bp算法,还有决策数的简单实现。
[myMatlabfenlei.rar] - matlab关于数据挖掘分类的算法,id3,c45,cart,sliq,调试运行成功,推荐下载,
[FractalDim.rar] - 盒维数MATLAB计算程序。%根据计盒维数原理编写了求一维曲线分形维数的matlab程序 function D=FractalDim(y,cellmax) %求输入一维信号的计盒分形维数 %y是一维信号 %cellmax:方格子的最大边长,可以取2的偶数次幂次(1,2,4,8..
[Svm.rar] - 统计模式识别、线性或非线性回归以及人工神经网络等方法是数据挖掘的有效工具,支持向量分类(support vector classification,简称SVC)算法是一个很有发展前景的方向。
[BPsimulationofpopulation.rar] - ”BP.m“文件是BP神经网络整个模型的源程序; “train.fig”是训练时最后得到的图片; “程序运行的人口数量原始数据.fig”是预测结果绘制的图; “程序运行时matlab命令窗口的内容.txt”是运行程序是在matlab命令窗口显示的东西; “程序运行完产生的数据.mat”是程序
[RBFnn.rar] - 径向基神经网络(Radial Basis Function, RBF)
[mycluster_KM_DS.rar] - 数据挖掘中的聚类算法,vc++实现,图形界面显示,直观清楚,很好,推荐下栽
[ycmatlab.rar] - 遗传算法程序是在 MATLAB环境下仿真的程序。可以在任何版本用的
[数据挖掘中CART算法实现.rar] - 数据挖掘中CART算法实现(用MATLAB实现)
[visa.rar] - 一个简单的数据挖掘程序,有贝叶斯方法和bp算法,还有决策数的简单实现。
[myMatlabfenlei.rar] - matlab关于数据挖掘分类的算法,id3,c45,cart,sliq,调试运行成功,推荐下载,
[FractalDim.rar] - 盒维数MATLAB计算程序。%根据计盒维数原理编写了求一维曲线分形维数的matlab程序 function D=FractalDim(y,cellmax) %求输入一维信号的计盒分形维数 %y是一维信号 %cellmax:方格子的最大边长,可以取2的偶数次幂次(1,2,4,8..
[Svm.rar] - 统计模式识别、线性或非线性回归以及人工神经网络等方法是数据挖掘的有效工具,支持向量分类(support vector classification,简称SVC)算法是一个很有发展前景的方向。
[BPsimulationofpopulation.rar] - ”BP.m“文件是BP神经网络整个模型的源程序; “train.fig”是训练时最后得到的图片; “程序运行的人口数量原始数据.fig”是预测结果绘制的图; “程序运行时matlab命令窗口的内容.txt”是运行程序是在matlab命令窗口显示的东西; “程序运行完产生的数据.mat”是程序
[RBFnn.rar] - 径向基神经网络(Radial Basis Function, RBF)
[mycluster_KM_DS.rar] - 数据挖掘中的聚类算法,vc++实现,图形界面显示,直观清楚,很好,推荐下栽
[ycmatlab.rar] - 遗传算法程序是在 MATLAB环境下仿真的程序。可以在任何版本用的
文件列表(点击判断是否您需要的文件):
mitmatlab

.........\Ada_Boost.m
.........\ADDC.m
.........\AGHC.m
.........\Backpropagation_Batch.m
.........\Backpropagation_CGD.m
.........\Backpropagation_Quickprop.m
.........\Backpropagation_Recurrent.m
.........\Backpropagation_SM.m
.........\Backpropagation_Stochastic.m
.........\Balanced_Winnow.m
.........\Bayesian_Model_Comparison.m
.........\Bhattacharyya.m
.........\BIMSEC.m
.........\C4_5.m
.........\calculate_error.m
.........\calculate_region.m
.........\CART.m
.........\CARTfunctions.m
.........\Cascade_Correlation.m
.........\Chernoff.m
.........\chess.mat
.........\Classification.txt
.........\classification_error.m
.........\classifier.m
.........\classifier.mat
.........\classifier_commands.m
.........\click_points.m
.........\clouds.mat
.........\Competitive_learning.m
.........\Components_without_DF.m
.........\Components_with_DF.m
.........\contents.m
.........\decision_region.m
.........\Deterministic_annealing.m
.........\Deterministic_Boltzmann.m
.........\Deterministic_SA.m
.........\Discrete_Bayes.m
.........\Discriminability.m
.........\DSLVQ.m
.........\EM.m
.........\enter_distributions.m
.........\enter_distributions.mat
.........\enter_distributions_commands.m
.........\feature_selection.m
.........\feature_selection.mat
.........\Feature_selection.txt
.........\feature_selection_commands.m
.........\FindParameters.m
.........\FindParameters.mat
.........\FindParametersFunctions.m
.........\FishersLinearDiscriminant.m
.........\fuzzy_k_means.m
.........\GaussianParameters.m
.........\GaussianParameters.mat
.........\generate_data_set.m
.........\Genetic_Algorithm.m
.........\Genetic_Culling.m
.........\Genetic_Programming.m
.........\Gibbs.m
.........\HDR.m
.........\high_histogram.m
.........\Ho_Kashyap.m
.........\ICA.m
.........\ID3.asv
.........\ID3.m
.........\index(1).htm
.........\index.htm
.........\Infomat.m
.........\Interactive_Learning.m
.........\Kohonen_SOFM.m
.........\Koller.m
.........\k_means.m
.........\Leader_Follower.m
.........\LMS.m
.........\load_file.m
.........\Local_Polynomial.m
.........\LocBoost.m
.........\LocBoostFunctions.m
.........\loglikelihood.m
.........\LS.m
.........\LVQ1.m
.........\LVQ3.m
.........\make_a_draw.m
.........\Marginalization.m
.........\MDS.m
.........\Minimum_Cost.m
.........\min_spanning_tree.m
.........\ML.m
.........\ML_diag.m
.........\ML_II.m
.........\multialgorithms.m
.........\multialgorithms.mat
.........\multialgorithms_commands.m
.........\Multivariate_Splines.m
.........\NDDF.m
.........\NearestNeighborEditing.m
.........\Nearest_Neighbor.m
.........\NLPCA.m
mitmatlab

.........\Ada_Boost.m
.........\ADDC.m
.........\AGHC.m
.........\Backpropagation_Batch.m
.........\Backpropagation_CGD.m
.........\Backpropagation_Quickprop.m
.........\Backpropagation_Recurrent.m
.........\Backpropagation_SM.m
.........\Backpropagation_Stochastic.m
.........\Balanced_Winnow.m
.........\Bayesian_Model_Comparison.m
.........\Bhattacharyya.m
.........\BIMSEC.m
.........\C4_5.m
.........\calculate_error.m
.........\calculate_region.m
.........\CART.m
.........\CARTfunctions.m
.........\Cascade_Correlation.m
.........\Chernoff.m
.........\chess.mat
.........\Classification.txt
.........\classification_error.m
.........\classifier.m
.........\classifier.mat
.........\classifier_commands.m
.........\click_points.m
.........\clouds.mat
.........\Competitive_learning.m
.........\Components_without_DF.m
.........\Components_with_DF.m
.........\contents.m
.........\decision_region.m
.........\Deterministic_annealing.m
.........\Deterministic_Boltzmann.m
.........\Deterministic_SA.m
.........\Discrete_Bayes.m
.........\Discriminability.m
.........\DSLVQ.m
.........\EM.m
.........\enter_distributions.m
.........\enter_distributions.mat
.........\enter_distributions_commands.m
.........\feature_selection.m
.........\feature_selection.mat
.........\Feature_selection.txt
.........\feature_selection_commands.m
.........\FindParameters.m
.........\FindParameters.mat
.........\FindParametersFunctions.m
.........\FishersLinearDiscriminant.m
.........\fuzzy_k_means.m
.........\GaussianParameters.m
.........\GaussianParameters.mat
.........\generate_data_set.m
.........\Genetic_Algorithm.m
.........\Genetic_Culling.m
.........\Genetic_Programming.m
.........\Gibbs.m
.........\HDR.m
.........\high_histogram.m
.........\Ho_Kashyap.m
.........\ICA.m
.........\ID3.asv
.........\ID3.m
.........\index(1).htm
.........\index.htm
.........\Infomat.m
.........\Interactive_Learning.m
.........\Kohonen_SOFM.m
.........\Koller.m
.........\k_means.m
.........\Leader_Follower.m
.........\LMS.m
.........\load_file.m
.........\Local_Polynomial.m
.........\LocBoost.m
.........\LocBoostFunctions.m
.........\loglikelihood.m
.........\LS.m
.........\LVQ1.m
.........\LVQ3.m
.........\make_a_draw.m
.........\Marginalization.m
.........\MDS.m
.........\Minimum_Cost.m
.........\min_spanning_tree.m
.........\ML.m
.........\ML_diag.m
.........\ML_II.m
.........\multialgorithms.m
.........\multialgorithms.mat
.........\multialgorithms_commands.m
.........\Multivariate_Splines.m
.........\NDDF.m
.........\NearestNeighborEditing.m
.........\Nearest_Neighbor.m
.........\NLPCA.m