资源简介
Matlab代码,好用的KNN代码,直接用
代码片段和文件信息
function rate = KNN(Train_dataTrain_labelTest_dataTest_labelkDistance_mark);
% K-Nearest-Neighbor classifier(K-NN classifier)
%Input:
% Train_dataTest_data are training data set and test data
% setrespectively.(Each row is a data point)
% Train_labelTest_label are column vectors.They are labels of training
% data set and test data setrespectively.
% k is the number of nearest neighbors
% Distance_mark : [‘Euclidean‘ ‘L2‘| ‘L1‘ | ‘Cos‘]
% ‘Cos‘ represents Cosine distance.
%Output:
% rate:Accuracy of K-NN classifier
%
% Examples:
%
% %Classification problem with three classes
% A = rand(50300);
% B = rand(50300)+2;
% C = rand(50300)+3;
% % label vector for the three classes
% gnd = [ones(3001);2*ones(3001);3*ones(3001)];
% fea = [A B C]‘;
% trainIdx = [1:150301:450601:750]‘;
% testIdx = [151:300451:600751:900]‘;
% fea_Train = fea(trainIdx:);
% gnd_Train = gnd(trainIdx);
% fea_Test = fea(testIdx:);
% gnd_Test = gnd(testIdx);
% rate = KNN(fea_Traingnd_Trainfea_Testgnd_Test1)
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%Reference:
%
% If you used my matlab code we appreciate it very much if you can cite our following papers:
% Jie Gui et al. “How to estimate the regularization parameter for spectral regression
% discriminant analysis and its kernel version?“ IEEE Transactions on Circuits and
% Systems for Video Technology (Accepted)
% Jie Gui Zhenan Sun Wei Jia Rongxiang Hu Yingke Lei and Shuiwang Ji “Discriminant
% Sparse Neighborhood Preserving embedding for Face Recognition“ Pattern Recognition
% vol. 45 no.8 pp. 2884–2893 2012 (SCI EI)
% Jie Gui Wei Jia Ling Zhu Shuling Wang and Deshuang Huang
% “Locality Preserving Discriminant Projections for Face and Palmprint Recognition“
% Neurocomputing vol. 73 no.13-15 pp. 2696-2707 2010
% Jie Gui et al. “Semi-supervised learning with local and global consistency“
% International Journal of Computer Mathematics (Accepted)
% Jie Gui Shu-Lin Wang and Ying-ke Lei “Multi-step Dimensionality Reduction and
% Semi-Supervised Graph-based Tumor Classification Using Gene expression
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