資源簡介
Matlab代碼,好用的KNN代碼,直接用
代碼片段和文件信息
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)
%
%
%
%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?
評論
共有 條評論