how to fix this code Error in fitcnb (line 250) this = Classifica​tionNaiveB​ayes.fit(X​,Y,Remaini​ngArgs{:})​; Error in PELATIHAN (line 74) Mdl = fitcnb(cha​in_code,ke​las_latih)​;

clc; clear; close all; warning off all;

%%% Proses Pelatihan

% Menetapkan lokasi folder data latih

nama_folder = 'DATA LATIH';

% membaca file citra

nama_file = dir(fullfile(nama_folder,'*.png*'));

% membaca jumlah file

jumlah_file = numel(nama_file);

% menginisialisasi variabel

chain_code = zeros(jumlah_file,8);

% melakukan pengolahan citra terhadap seluruh file

for n = 1:jumlah_file

% membaca file citra

A = imread(fullfile(nama_folder,nama_file(n).name));

%figure, imshow(A)ciri_latih

% RGB to Grayscale

B = rgb2gray(A);

%figure, imshow(B)

% deteksi tepi sobel

C=double(B);

sobelhor = [-1 0 1; -2 0 2; -1 0 1];

sobelver = [-1 -2 -1; 0 0 0; 1 2 1];

I1 = conv2(C,sobelhor,'same');

I2 = conv2(C,sobelver,'same');

D = sqrt((I1.^2)+(I2.^2));

D = uint8(D);

%figure, imshow(D)

% Threshold

E = imbinarize(D,.3);

%figure, imshow(E)

% operasi opening

F = bwareaopen(E,100);

%figure, imshow(F)

boundaries = bwboundaries(F);

% ekstraksi fitur

CC = cell(1,length(boundaries));

for k = 1:length(boundaries)

CC{k} = chaincode(boundaries{k});

end

chain_code(n,1) = sum(CC{1,1}.code==0);

chain_code(n,2) = sum(CC{1,1}.code==1);

chain_code(n,3) = sum(CC{1,1}.code==2);

chain_code(n,4) = sum(CC{1,1}.code==3);

chain_code(n,5) = sum(CC{1,1}.code==4);

chain_code(n,6) = sum(CC{1,1}.code==5);

chain_code(n,7) = sum(CC{1,1}.code==6);

chain_code(n,8) = sum(CC{1,1}.code==7);

% menyusun variabel kelas_latih

kelas_latih = cell(jumlah_file,1);

% mengisi nama-nama huruf pada variabel kelas_latih

for k = 1:3

kelas_latih{k} = 'A';

end

for k = 4:5

kelas_latih{k} = 'B';

end

for k = 6:7

kelas_latih{k} = 'C';

end

% klasifikasi cita menggunakan algoritma naive bayes

Mdl = fitcnb(chain_code,kelas_latih);

% membaca kelas keluaran hasil pelatihan

hasil_latih = predict(Mdl,chain_code);

end

Error in fitcnb (line 250)

this = ClassificationNaiveBayes.fit(X,Y,RemainingArgs{:});

Error in PELATIHAN (line 74)

Mdl = fitcnb(chain_code,kelas_latih);