Error in HeatMap, In following code confusion matrix is plotted but i want to visualize the same using a heat map, what is wrong?

Error using HeatMap/set Invalid parameter/value pair arguments.

Error in HeatMap (line 392) set(obj, pvPairs{:});

Error in maintotaldemo (line 78) HeatMap(Conf_Mat, test_label, test_label, 1,'Colormap','red','ShowAllTicks',1,'UseLogColorMap',true,'Colorbar',true);

clear all; clc;

%% BUILD DORSAL HAND VEIN TEMPLATE DATABASE

%% load mat files

 load('db1.mat');
 load('db2.mat');

 %%reshape into row vector

reduced_testdata = reshape(reduced_testdata,1,4,20); % one row,four column and 15(60/4) group for 20 classes reduced_traindata = reshape(reduced_traindata,1,4,40); % 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'; % % %%% if classes are 20 then eiganvectors not exceed then 179 % model = perform_pca(P_train,rank(P_train)-1); %rank(P_train)-1 % % test_features= linear_subspace_projection(P_test, model, 1); % P_train=model.train'; % P_test=test_features';

%% classfication

predictlabel = knnclassify(P_test, P_train, train_label,3,'euclidean','nearest'); cp = classperf(test_label,predictlabel);

% mdl = fitcknn(P_train,train_label,'Distance','euclidean','NumNeighbors',3); % predictlabel = predict(mdl,P_test);

Conf_Mat = confusionmat(test_label,predictlabel); disp(Conf_Mat) HeatMap(Conf_Mat, test_label, test_label, 1,'Colormap','red','ShowAllTicks',1,'UseLogColorMap',true,'Colorbar',true);

%% % Evaluate performance

 [FPR, TPR,Thr, AUC, OPTROCPT]  = perfcurve(predictlabel, test_label,1);

 plot(TPR,FPR,'--rs','LineWidth',2,'MarkerEdgeColor','k','MarkerFaceColor','g','MarkerSize',10)
 figure,
 plot(TPR,FPR,'r-','LineWidth',4);
 xlabel('False positive rate')
 ylabel('True positive rate') 
 title('ROC Curve for Classification ')
 Tbl = table(FPR, TPR,Thr)

%% FAR = FPR = FP/(FP + TN) and FRR = FNR = FN/(FN + TP)

[FPR, FNR,Thr] = perfcurve(predictlabel, test_label,1,'xCrit','FPR','yCrit','FNR','TVals','all'); Thr = Thr/10; figure, plot(Thr,FPR,'r--','LineWidth',2,'MarkerEdgeColor','k','MarkerFaceColor','g','MarkerSize',10); xlabel('Threshold') ylabel('False positive rate / FAR') title('ROC Curve for Classification ')

 figure,
 plot(Thr,FNR,'r--','LineWidth',2,'MarkerEdgeColor','k','MarkerFaceColor','g','MarkerSize',10);
 xlabel('Threshold')
 ylabel('False Negative rate / FRR') 
 title('ROC Curve for Classification ')
 Tbl = table(FPR, FNR,Thr) 

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