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

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Negar Bassiri 2021-9-10

评论： Negar Bassiri 2021-9-10

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

Hints:

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

nonlinear optimization (

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

Negar Bassiri 2021-9-10

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

Negar Bassiri 2021-9-10

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

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