Description: 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. Platform: |
Size: 2048 |
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Description: 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. Platform: |
Size: 6144 |
Author:yuanxin |
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Description: 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 Platform: |
Size: 5120 |
Author:taotao |
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Description: 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.) Platform: |
Size: 362496 |
Author:pluto1888 |
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