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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

Iris数据的最近邻分类与k近邻分类程序,以及5路交叉验证,适合于新手学习,附有数据集-And nearest neighbor classification k-nearest neighbor classification procedure Iris data, as well as 5-way cross-validation, suitable for novices to learn, with data collection
Date : Size : 5kb User : taotao

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pls交叉验证,可自行设定K-folder交叉验证(pls cross validation)
Date : Size : 6kb User : djdy

SURROGATES工具箱是一个多维函数逼近和优化方法的通用MATLAB库。当前版本包括以下功能: 实验设计:中心复合设计,全因子设计,拉丁超立方体设计,D-optimal和maxmin设计。 代理:克里金法,多项式响应面,径向基神经网络和支持向量回归。 错误和交叉验证的分析:留一法和k折交叉验证,以及经典的错误分析(确定系数,标准误差;均方根误差等;)。 基于代理的优化:高效的全局优化(EGO)算法。 其他能力:通过安全裕度进行全局敏感性分析和保守替代。(SURROGATES Toolbox is a general-purpose MATLAB library of multidimensional function approximation and optimization methods. The current version includes the following capabilities: Design of experiments: central composite design, full factorial design, Latin hypercube design, D-optimal and maxmin designs. Surrogates: kriging, polynomial response surface, radial basis neural network, and support vector regression. Analysis of error and cross validation: leave-one-out and k-fold cross-validation, and classical error analysis (coefficient of determination, standard error; root mean square error; and others). Surrogate-based optimization: efficient global optimization (EGO) algorithm. Other capabilities: global sensitivity analysis and conservative surrogates via safety margin.)
Date : Size : 354kb User : pluto1888
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