There is some error while calling function fitcknn. I passed parameters like fitcknn(P_​train,trai​n_label,'D​istance','​euclidean'​,'NumNeigh​bors',5) here size of P_train is 176 X 180 and train_label is 180 1

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Error using classreg.learning.FullClassificationRegressionModel.prepareDataCR (line 201)
X and Y do not have the same number of observations.
Error in classreg.learning.classif.FullClassificationModel.prepareData (line 487)
classreg.learning.FullClassificationRegressionModel.prepareDataCR(...
Error in ClassificationKNN.prepareData (line 868)
prepareData@classreg.learning.classif.FullClassificationModel(X,Y,varargin{:},'OrdinalIsCategorical',true);
Error in classreg.learning.FitTemplate/fit (line 213)
this.PrepareData(X,Y,this.BaseFitObjectArgs{:});
Error in ClassificationKNN.fit (line 853)
this = fit(temp,X,Y);
Error in fitcknn (line 315)
this = ClassificationKNN.fit(X,Y,RemainingArgs{:});
Error in main_new (line 621)
mdl = fitcknn(P_train,train_label,'Distance','euclidean','NumNeighbors',5);
-----
%%Code%%%%%%%%%%%%%%%
%%Dorsal hand vein recognition using SVM
clc
clear all;
c=[];
addpath train;
addpath test;
mapping=getmapping(8,'u2'); %LBP
% W=[2,1,1,1,1,1,2; ...
% 2,4,4,1,4,4,2; ...
% 1,1,1,0,1,1,1; ...
% 0,1,1,0,1,1,0; ...
% 0,1,1,1,1,1,0; ...
% 0,1,1,2,1,1,0; ...
% 0,1,1,1,1,1,0];
W=[0,0,0,0,0,0,0; ...
0,1,1,1,1,1,0; ...
0,1,2,4,2,1,0; ...
0,1,4,4,4,1,0; ...
0,1,2,4,2,1,0; ...
0,1,1,1,1,1,0; ...
0,0,0,0,0,0,0];
for i=1:9
B=imread(strcat('train\','1\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','2\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','3\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','4\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','5\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','6\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','7\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','8\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','9\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','10\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','11\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','12\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','13\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','14\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','15\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','16\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','17\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','18\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','19\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
for i=1:9
B=imread(strcat('train\','20\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
% imshow(lpqhist);
a=[H2,lpqhist];
c=[c;a];
disp(sprintf('Done',i));
end
d=[];
for i=1:3
B=imread(strcat('test\','1\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','2\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','3\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','4\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','5\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','6\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','7\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','8\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','9\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','10\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','11\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','12\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','13\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','14\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','15\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','16\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','17\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','18\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','19\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
for i=1:3
B=imread(strcat('test\','20\',num2str(i),'.bmp'));
X = double(B);
X = imresize(X,[60 60],'bilinear');
H2=DSLBP(X,mapping,W);
Gray=X;
Gray=(Gray-mean(Gray(:)))/std(Gray(:))*20+60;
lpqhist=lpq(Gray,3,1,1,'nh');
a=[H2,lpqhist];
d=[d;a];
disp(sprintf('Done',i));
end
P_train=c;
P_test=d;
% %%PCA low dimension reduction
%
P_train = P_train';
model = perform_pca(P_train,rank(P_train)-1);
test_features= linear_subspace_projection(P_test, model, 1);
P_train=model.train';
P_test=test_features';
%%Normalisation
P_train=P_train/256;
P_test=P_test/256;
% %%%%%%%%load label %%%%%%%%%%%%
train_label=load('train_label.txt');
test_label=load('test_label.txt');
P_train = P_train';
P_test = P_test';
%%classification K Nearest Neighour
% results = nn_classification_PhD(P_train,train_label, P_test, test_label, size(P_test,1), 'euc');
mdl = fitcknn(P_train,train_label,'Distance','euclidean','NumNeighbors',5);
predict_label = predict(mdl,P_test);

Accepted Answer

Walter Roberson
Walter Roberson on 28 Mar 2018
"Predictor data, specified as numeric matrix.
Each row corresponds to one observation (also known as an instance or example), and each column corresponds to one predictor variable (also known as a feature).
The length of Y and the number of rows of X must be equal."
So, you are passing in X data that has 176 samples, each with 180 features, but you are passing in 180 feature labels.
Chances are that you want to pass in X.'
  7 Comments
Balaji M. Sontakke
Balaji M. Sontakke on 31 Mar 2018
Sir, In this function [predict_label,score,cost] = predict(mdl,P_test); the score matrix contains o and 1 values but how to see a matrix contains distances.

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