Useing “ga” function in MATLAB to use Genetic Algorithm for nonlinear optimization

draws a line that separates the positive examples (shown as ‘+’ symbols in the plot) from

the negative examples (shown as ‘o’ symbols in the plot). The resulting line is

your trained classifier for the given input data.

% we need to Define an underlying function (line) in 2D

a=?; b=?;

hold on;

% Generate 20 random examples

N=20;

for i=1:N

x = rand(1)*5; y = rand(1)*5;

data(i,:) = [x y]; % Generate random coordinates

% Saves the coordinates

if (y > a*x + b )% If the point is above the line

label(i) = 1; plot(x,y,'r+'); % Make it a positive example

else

label(i) = -1; plot(x,y,'go'); % Otherwise, make it negative

end

end

Hints:

1. You can use “ga” function in MATLAB to use Genetic Algorithm for

nonlinear optimization (

https://www.mathworks.com/help/gads/ga.html)

[Steven Lord]

This sounds like a homework assignment. If it is, show us the code you've written to try to solve the problem and ask a specific question about where you're having difficulty and we may be able to provide some guidance.

If you aren't sure where to start because you're not familiar with how to write MATLAB code, I suggest you start with the MATLAB Onramp tutorial (https://www.mathworks.com/support/learn-with-matlab-tutorials.html) to quickly learn the essentials of MATLAB.

If you aren't sure where to start because you're not familiar with the mathematics you'll need to solve the problem, I recommend asking your professor and/or teaching assistant for help.

[Negar Bassiri]

myRand:

function[label, x ,y] = myRand(opt)

% Define an underlying function (line) in 2D

a=opt(1);

b=opt(2);

% Generate 20 random examples

for i = 1:20

x = rand(1)*5; y = rand(1)*5; % Generate random coordinates

if (y > a*x + b )% If the point is above the line

label(i) = 1; % Make it a positive example

else

label(i) = -1; % Otherwise, make it negative

end

end

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

code:

hold on

A = [1 1];

b = [1];

Aeq = [];

beq = [];

lb = 0;

ub = 5;

myRand(x)

options = optimoptions('ga','PlotFcn', @gaplotbestf);

rng default % For reproducibility

fun = @(x) myRand(x)

x = ga(fun,2,A,b,[],[],[],lb,ub,options)

[Steven Lord]

Thank you for showing your code. Now what is the specific question you have about this code or issue that you're experiencing when you try to use this code to solve the problem?

[Negar Bassiri]

this code needs one input for @gaplotbestf and myRand is giving out 20*2 output. I dont know how to colve it.

[Negar Bassiri]

hi, do you want to help or ask question. becuase I have my dealine around the corner.