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本次大作业利用K‐近邻（K‐Nearest Neighbor）算法，为给定的训练数据集构造了分类器，
并在测试数据集上进行分类预测，同时计算了Accuracy、Precision、Recall和F‐measure，利用
10‐fold的实验方法进行交叉验证。-The big job to use K-neighbor (K-Nearest Neighbor) algorithm, for a given set of training data classifier is constru
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模式识别某次课程的作业，完成了高斯分布下的两种贝叶斯分类器,以及非参数的K近邻、Parzen窗方法，采用UCI机器学习数据库中的某些数据作为样本，使用交叉验证方法确定参数-Pattern recognition of a particular course work, completed under the two Gaussian Bayesian classifier, and the non-parametric K-nearest neighbor, Parzen window meth
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MATLAB cross-validation tool for classification and regression v0.1
FEATURES:
+ K-fold cross validation.
+ Arbitrary train and prediction functions with parameters can be used.
+ Arbitrary loss function can be used.
+ Wrappers for
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分别采用GMM和KDE对Iris数据集进行密度建模，并进行对比。通过EM算法来确定GMM参数，通过交叉验证来确定K值-GMM and KDE respectively Iris data set of density modeling, and compared. GMM by EM algorithm to determine the parameters of K determined by the value of cross-validation
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Feature selection methods for machine learning algorithms such as SVR, including one filter-based method (CFS) and two wrapper-based methods (GA and PSO). The gridsearch is for the grid search for the optimal hyperparemeters of SVR. The SVM_CV is for
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matlab交叉验证cross Validation，把样本集分为训练集和测试集，防止网络出现过拟合，提高网络的泛化能力和预测精度-cross Validation for matlab，to estimate the test accuracy,training accuray and validation accuracy of a neural network
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一个matlab写的bp人工神经网络程序，参数优化采用交叉验证办法-Write a matlab bp artificial neural network program, parameter optimization using cross-validation method
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机器学习大牛Dale Schuurmans写的多类SVMs的快速实现算法，可以自己修改核函数，通过K-fold cross validation训练得到最优参数，分类效果很好-Machine learning large cattle Dale Schuurmans write multi-class SVMs fast algorithm, can modify the kernel function, the optimal parameters through K-fold cross v
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Implement the K nearest neighbor algorithm by your own instead of using available software.
2. Use K-fold cross validation to generate training and testing datasets. You should try different K values (3~8) to see how they affect your result.
3. T
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用matlab实现Part1. 实现一个k近邻分类器，Part 2.实现一个最小二乘分类器，Part 3.实现一个支持向量机分类器，Part 4.在不同数据集上使用交叉验证选择各个算法的参数-Part1. Achieve a k-nearest neighbor classifier, Part 2. Achieve a least-squares classifier, Part 3. Implement a support vector machine classifier, Part 4.
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k近邻分类器分类 包括PCA功能 归一化 并且带有交叉检验功能-k nearest neighbor classifiers including PCA function normalized and with cross-validation function
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Divide/Create data into K-Folds training and testing data which are balanced basing on the labels. It is for k-fold cross validation.
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matlab编写的调整svm参数的程序，其中cross是主程序，另两个是自己编写的svm核函数，如果要用matlab自带的核函数就把-t的值改成2即可。Ytrain是标记矩阵，Xtrain是特征矩阵，都由用户自己导入。可利用k倍交叉验证来选择最优的c参数。k可自行更改。-svm matlab prepared to adjust the parameters of the program, which cross the main program, and the other two are t
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ann k-fold cross validation matlab cone
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SVM with K-fold cross validation
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以著名的wine数据作为实验样本。包括k-NN算法，交叉验证，PCA降维等。-With the famous wine data as experimental samples.K- NN algorithm, cross validation, PCA dimension reduction, etc.
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code for lvq and split the data to be train and test by k-fold cross validation with k=5
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统计模式识别工具箱(STPRTool 版本2.12 2013-09-12) 功能有线性判别函数、特征提取、密度估计和聚类、支持向量机、贝叶斯分类器、交叉验证等-Statistical Pattern Recognition Toolbox
Methods:
Fisher,PCA,GMM,K-means,SVM,Bayes classifier,Cross-validation,KNN,etc.
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K近邻分类器，实现了对iris数据集的分类，并且使用了交叉验证的方法，来验证求得的最优的K值。-K-nearest neighbor classifier to achieve the classification of iris data set and cross-validation of the method used to verify the optimal value of K obtained.
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进行K折交叉验证，将数据分为K份，将1份作为TEST，剩下K-1份作为TRAINING，对TEST进行测试(K folding cross validation)
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