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模式识别中pca 5-fold交叉检验算法-pattern recognition pca 5-fold cross-validation algorithm
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基于NSVM的两类SVM分类器,matlab7.1运行通过,main中做了PCA的特征提取、leave one out cross-valiation和5-fold cross-validation(重复10次的平均值)
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神经网络训练,应用matlab7NN包,用一个隐藏层使用5折交叉验证。-Training the Neural Network
This scr ipt is something that I did for a course at Uni. It uses the Neural Networking package provided with MatLab 7 unfortunately I m not sure if it s available with the earlier ve
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estimate the test accuracy,training accuray and validation accuracy of a neural network with 10-fold cross validation.-estimate the test accuracy,training accuray and validation accuracy of a neural network with 10-fold cross validation.
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Matlab 实现多项式曲线拟合(正弦曲线),交叉验证(十折交叉验证)-poly fit ,cross validation
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非常好的5倍交叉验证的程序,可以进行svm分类,推荐大家使用,非常好的-Very good 5-fold cross-validation procedure, svm classification, we recommend using the very good
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1、 极大似然估计
尝试用0~24阶多项式拟合,并用5折交叉验证选择最佳模型(多项式阶数及其系数,给出类似课件中的图),并画出最佳模型的拟合效果图(类似图1,蓝色点为训练样本、红色点为测试样本、绿色线为模型预测),给出该模型的测试误差。
2、 岭回归
多项式阶数为24,正则系数λ的取值范围为exp(-19)到exp(20),采用并用5折交叉验证选择最佳模型。实验结果要求同1。
-1, the maximum likelihood estimate of 0 to 24 try-o
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使用Python实现朴素贝叶斯分类,文件夹中附带数据集。实现了NB算法,并进行5倍交叉验证-Naive Bayes classifier using the Python implementation, the folder with the data set. NB implements the algorithm, and 5-fold cross-validation
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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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在机器学习中利用欧氏距离设计一个KNN分类器,实现五折交叉验证,并用PCA进行降维-Develop a k-NN classifier with Euclidean distance and simple voting.Perform 5-fold cross validation, find out which k performs the best (in terms of accuracy)。Use PCA to reduce the dimensionality to 6, then p
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内有鸢尾花数据的5折交叉验证实验代码,采用的分类器是贝叶斯分类器。(There is a 5-fold cross-validation experiment code for the iris data, and the classifier used is a Bayesian classifier.)
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