Useing “ga” function in MATLAB to use Genetic Algorithm for nonlinear optimization
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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)
5 个评论
Steven Lord
2021-9-10
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
2021-9-10
Steven Lord
2021-9-10
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
2021-9-10
Negar Bassiri
2021-9-10
回答(0 个)
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