The method of random disturbance of training samples in matlab, matlab Samples

The method of random disturbance of training samples in matlab, matlab Samples

Use randperm () to generate random seeds, and then swap locations for random sample extraction.

Official content:

The built-in function randperm (n) of Matlab generates random orders of integers ranging from 1 to n without duplicates. Then, we can use it to obtain random numbers without duplicates.
Function p = randperm (n );
% RANDPERM Random permutation.
% RANDPERM (n) is a random permutation of the integers from 1 to n.
% For example, RANDPERM (6) might be [2 4 5 6 1 3].
%
% Note that randperm cils rand and therefore changes RAND's state. %
% See also PERMUTE. % Copyright 1984-2002 The MathWorks, Inc.
% $ Revision: 5.10 $ Date: 2002/04/09 00:26:14 $
[Ignore, p] = sort (rand (1, n ));

Principle:
1. rand (1, n) generates a random number matrix within 0-1 of n columns in 1 row.
2. sort () sorts this matrix. The returned ignore is the sorted sequence, and p is the original index of the number of sorted sequences. This index must be random, and there is no repeated integer between 1 and n.

Code:

> A = rand (10, 4) a = 0.9516 0.3015 0.0326 0.6448 0.9203 0.7011 0.5612 0.3763 0.0527 0.6663 0.8819 0.1909 0.7379 0.5391 0.6692 0.4283 0.2691 0.6981 0.1904 0.4820 0.4228 0.6665 0.3689 0.1206 0.5479 0.1781 0.4607 0.5895 0.9427 0.1280 0.9816 0.2262 0.4177 0.9991 0.1564 0.3846 0.9831 0.1711 0.8555 0.5830> RandIndex = randperm (length ()); % then the array index a = a (RandIndex ,:); % create an array with new indexes> aa = 0.9831 0.1711 0.8555 0.5830 0.9516 0.3015 0.0326 0.6448 0.7379 0.5391 0.6692 0.4283 0.9203 0.7011 0.5612 0.3763 0.9427 0.1280 0.9816 0.2262 0.4177 0.9991 0.1564 0.3846 0.0527 0.6663 0.8819 0.1909 0.5479 0.1781 0.4607 0.5895 0.2691 0.6981 0.1904 0.4820 0.4228 0.6665 0.3689 0.1206