Error during classification using SVM

Error using svmtrain (line 234)

Y must be a vector or a character array.

Error in inv_Moment_maintotaldemo (line 86)

model=svmtrain(train_label,P_train);

clear all;

clc;

%% BUILD DORSAL HAND VEIN TEMPLATE DATABASE

tic; %% calculating elapsed time for execution

%% load mat files

load('db3.mat');

load('db4.mat');

%% reshape into row vector

reduced_testdata = reshape(reduced_testdata,1,4,10); % one row,four column and 15(60/4) group for 20 classes

reduced_traindata = reshape(reduced_traindata,1,4,20); % one row,four column and 45(180/4) group for 20 classes

%% adjust dimension

% Adjust matrix dimension

P_test = cell2mat(reduced_testdata); % Convert cell array to matrix

P_train = cell2mat(reduced_traindata);

%% rearranges the dimensions of P_test and P_train

C = permute(P_test,[1 3 2]);

P_test = reshape(C,[],size(P_test,2),1);

C = permute(P_train,[1 3 2]);

P_train = reshape(C,[],size(P_train,2),1);

%% labeling class

train_label=load('train_label.txt');

test_label=load('test_label.txt');

% %%% Normalisation

%

% P_train=P_train/256;

% P_test=P_test/256;

%% Normalisation by min max

P_train=mapminmax(P_train,0,1);

P_test=mapminmax(P_test,0,1);

%% Normalisation by Z - Scores

% P_train = zscore(P_train,0,2);

% P_test =zscore(P_test,0,2);

%% %%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';

%% SVM classifier

model=svmtrain(train_label,P_train);

[predicted_label, accuracy, decision_values]=predict(test_label,P_test,model);

[FPR, TPR,Thr, AUC, OPTROCPT] = perfcurve(predictlabel, test_label,3);

figure,

plot(TPR,FPR,'r-','LineWidth',1);

xlabel('False positive rate')

ylabel('True positive rate')

title('ROC Curve for Classification ')

Tbl = table(FPR, TPR,Thr)

fprintf('\n\n Overall accuracy:%f%%\n',cp.CorrectRate*100);

%% calculating elapsed time for execution

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