KNN classification accuracy problem

In my program accuracy is not increases I have given properly traning and testing input to knn classifier. I got following result, how I increase the accuracy rate?

Accuracy: 0.1125

Error: 0.8875

Sensitivity: 0.1125

Specificity: 0.9533

Precision: 0.1101

FalsePositiveRate: 0.0467

F1_score: NaN

MatthewsCorrelationCoefficient: 0.1179

Kappa: 0.8930

clear all;

clc;

%% BUILD DORSAL HAND VEIN TEMPLATE DATABASE

tic; %% calculating elapsed time for execution

%% load mat files

load('db1.mat');

load('db2.mat');

%% reshape into row vector for 100 classes

%% reshape into row vector for 10 classes

reduced_testdata = reshape(reduced_testdata,1,2,40); % one row,four column and 15(60/4) group for 20 classes

reduced_traindata = reshape(reduced_traindata,1,2,80); % 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);

%'euclidean'; 'cityblock'; 'chebychev'; 'minkowski'; 'cosine'; 'correlation'; 'spearman'; 'hamming'; 'jaccard'; 'squaredeuclidean'

predictlabel = knnclassify(P_test, P_train, train_label,1,'euclidean','nearest');

%

cp = classperf(test_label,predictlabel);

% % % % %

Conf_Mat = confusionmat(test_label, predictlabel);

disp(Conf_Mat);

%

%

% disp('_____________Multiclass demo_______________')

% disp('Runing Multiclass confusionmat')

%

[c_matrix,Result,RefereceResult]= confusion.getMatrix(test_label,predictlabel);

%% calculating elapsed time for execution

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