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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 constructed, and the test data sets to classify forecasts, while the calculation of the Accuracy, Precision, Recall and F-measure , using 10-fold cross-validation of experimental methods.
Date : Size : 987kb User : andy

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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 method, using UCI machine learning database as sample some of the data, using cross-validation method to determine the parameters
Date : Size : 1.09mb User : libo

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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
Date : Size : 98kb User : lifei

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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 validation training classification works well
Date : Size : 3kb User : wang

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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
Date : Size : 139kb User : 朱戎生

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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.
Date : Size : 18kb User : Zhuzhiwei

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.
Date : Size : 5.76mb User : lee

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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.
Date : Size : 2kb User :

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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 perform 2) again.
Date : Size : 6kb User : yuanxin
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