From the Matlab command window download the iris dataset using the load command: load ('fisheriris.mat'). This will download two variables. The species and meas. The former contains the list of species or types of the iris. However, the latter is a double matrix with 4 features and 150 data samples. You are required to do the followings:

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 Answer & Explanation

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Properly labelled MATLAB code and the figures are attached in the explanation. Please run this code to get answers to all parts.

Answer to Part 4 : From figures it seems that features 2&3 and 3&4 can be used to separate the colors as different color points corresponding to flowers of different species have very less overlap in figure 2 and figure 3.

Step-by-step explanation

clear all

clc

close all

load ('fisheriris.mat')

 

idx_setosa = strcmp(species,'setosa');

idx_versicolor = strcmp(species,'versicolor');

idx_virginica = strcmp(species,'virginica');

%% PART 1

figure;

plot(meas(idx_setosa,1),meas(idx_setosa,2),'ro','LineStyle','none')

hold on

plot(meas(idx_versicolor,1),meas(idx_versicolor,2),'bs','LineStyle','none')

plot(meas(idx_virginica,1),meas(idx_virginica,2),'g*','LineStyle','none')

legend('setosa','versicolor','virginica')

xlabel('Feature 1')

ylabel('Feature 2')

%% PART 2

figure;

plot(meas(idx_setosa,2),meas(idx_setosa,3),'ro','LineStyle','none')

hold on

plot(meas(idx_versicolor,2),meas(idx_versicolor,3),'bs','LineStyle','none')

plot(meas(idx_virginica,2),meas(idx_virginica,3),'g*','LineStyle','none')

legend('setosa','versicolor','virginica')

xlabel('Feature 2')

ylabel('Feature 3')

%% PART 3

figure;

plot(meas(idx_setosa,3),meas(idx_setosa,4),'ro','LineStyle','none')

hold on

plot(meas(idx_versicolor,3),meas(idx_versicolor,4),'bs','LineStyle','none')

plot(meas(idx_virginica,3),meas(idx_virginica,4),'g*','LineStyle','none')

legend('setosa','versicolor','virginica')

xlabel('Feature 3')

ylabel('Feature 4')

 %% PART 4

%

 

%% PART5 - Euclidean distance calu=culation

Dist = zeros(length(species),length(species));

for i = 1:length(species)

  for j = 1:length(species)

    Dist(i,j) = myEucDis(meas(i,:),meas(j,:));%distance between ith and jth data sample

  end

end

% Dist is the matrix whose (i,j)th element is the euclidean distance

% between features of ith and jth iris flower in he datasample

%% PART6 - Mean calculation

Mean_setosa = mean(meas(idx_setosa,:)); %mean of individual features for setosa iris

Mean_versicolor = mean(meas(idx_versicolor,:)); %mean of individual features for versicolor iris

Mean_virginica = mean(meas(idx_virginica,:)); %mean of individual features for virginica iris

 

%%% MATLAB FUNCTION FILE

function dis = myEucDis(pt1,pt2)

%calulates euclidean distance between one data sample and the other

dis = sqrt(sum((pt1-pt2).*(pt1-pt2)));

end