Hello guys.. I am currently doing project on raw data analysis of smell pattern.. the data is being analysed via pca,hca, and lda.. I already completed on PCA.. I need your help on HCA as it shows dimension mismatcH. tHIS IS MY PROGRAM.

clear all; clear; clc

%call data d1=xlsread('amb010611.csv');

d2=xlsread('banana010611.csv');

d3=xlsread('rose010611.csv');

d4=xlsread('strawberry010611.csv');

d5=xlsread('Vanilla010611.csv');

%filter data

data1 = d1(101:600,1:12);

data2 = d2(101:600,1:12);

data3 = d3(101:600,1:12);

data4 = d4(101:600,1:12);

data5 = d5(101:600,1:12);

%filter data for 500 samples, from 1 to 12 sensor.

%digital filter data

data1s=sgolayfilt(data1,2,11);

data2s=sgolayfilt(data2,2,11);

data3s=sgolayfilt(data3,2,11);

data4s=sgolayfilt(data4,2,11);

data5s=sgolayfilt(data5,2,11);

%average mean data ambience

mean_data1s=mean(data1s);

%average mean data ambience minus with data collected

k2=size(data2s); coloum2=k2(2); rows2=k2(1); for i = 1:rows2 for j=1:coloum2 data2bl(i,j)= data2s(i,j) - mean_data1s(1,j); end end

k3=size(data3s); coloum3=k3(2); rows3=k3(1); for i = 1:rows3 for j=1:coloum3 data3bl(i,j)= data3s(i,j) - mean_data1s(1,j); end end

k4=size(data4s); coloum4=k4(2); rows4=k4(1); for i = 1:rows4 for j=1:coloum4 data4bl(i,j)= data4s(i,j) - mean_data1s(1,j); end end

k5=size(data5s); coloum5=k5(2); rows5=k5(1); for i = 1:rows5 for j=1:coloum5 data5bl(i,j)= data5s(i,j) - mean_data1s(1,j); end end

%PCA comparison

x = [data2bl;data3bl;data4bl;data5bl];

[alfa,pc,eigcov,tsq] = princomp(x);

percent_explained = 100*eigcov/sum(eigcov); PC1 = percent_explained(1) PC2 = percent_explained(2)

%PCA plotting

figure(11); plot(pc(1:500,1), pc(1:500,2),'ro');hold on;

plot(pc(501:1000,1), pc(501:1000,2),'b*');

plot(pc(1001:1500,1), pc(1001:1500,2),'ks');

plot(pc(1501:2000,1), pc(1501:2000,2),'y>'); %

%PCA percentage plotting title('2D PCA Plot');

xlabel('PC1 (87.2567%)');

ylabel('PC2 (10.1872%)');

grid on;

h = legend('Banana','Rose','Strawberry','Vanilla',2);

%HCA PROGRAMMING

z=zeros(250,10); z=[data2bl(1:50,:); data3bl(1:50,:); data4bl(1:50,:); data5bl(1:50,:);]; for index=1:50 Origin(index,:)='Banana'; end for index=51:100 Origin(index,:)='Rose'; end for index=101:150 Origin(index,:)='Strawerry'; end for index=151:200 Origin(index,:)='Vanilla'; end

%Dendrogram plot figure(12) [d,p,stats]= manova1(z,Origin); manovacluster(stats,'single'); title('Dendrogram plot of Basic Smell'); ylabel('Similarity level'); xlabel('Sample type') grid on; h=legend('Banana','Rose','Strawberry','Vanilla',2);