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6 functions for generating artificial datasets

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6 parameterized functions that generate distinct 2D datasets for Machine Learning purposes.

twospirals(N, degrees, start, noise)
function data = twospirals(N, degrees, start, noise)
% Generate "two spirals" dataset with N instances.
% degrees controls the length of the spirals
% start determines how far from the origin the spirals start, in degrees
% noise displaces the instances from the spiral. 
%  0 is no noise, at 1 the spirals will start overlapping

    if nargin < 1
        N = 2000;
    end
    if nargin < 2
        degrees = 570;
    end
    if nargin < 3
        start = 90;
    end
    if nargin < 5
        noise = 0.2;
    end  
    
    deg2rad = (2*pi)/360;
    start = start * deg2rad;

    N1 = floor(N/2);
    N2 = N-N1;
    
    n = start + sqrt(rand(N1,1)) * degrees * deg2rad;   
    d1 = [-cos(n).*n + rand(N1,1)*noise sin(n).*n+rand(N1,1)*noise zeros(N1,1)];
    
    n = start + sqrt(rand(N1,1)) * degrees * deg2rad;      
    d2 = [cos(n).*n+rand(N2,1)*noise -sin(n).*n+rand(N2,1)*noise ones(N2,1)];
    
    data = [d1;d2];
end

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