I am using t-SNE with the matlab code from this web site (https://lvdmaaten.github.io/tsne/). However, there is an error whenever I run this program with the data's dimension is larger than the number of data. The code below is the code I use currently and the error is always occurs here
M = M(:,ind(1:initial_dims));
the error is
Index exceeds matrix dimensions.
Error in tsne (line 62)
M = M(:,ind(1:initial_dims));
I call this tsne function with the command in the matlab
output = tsne(input, [], 2, 640, 30);
The input size is (162x640), the dimension is 640 and the number of data is 162. The program below is the code from the website above.
function ydata = tsne(X, labels, no_dims, initial_dims, perplexity)
%TSNE Performs symmetric t-SNE on dataset X
%
% mappedX = tsne(X, labels, no_dims, initial_dims, perplexity)
% mappedX = tsne(X, labels, initial_solution, perplexity)
%
% The function performs symmetric t-SNE on the NxD dataset X to reduce its
% dimensionality to no_dims dimensions (default = 2). The data is
% preprocessed using PCA, reducing the dimensionality to initial_dims
% dimensions (default = 30). Alternatively, an initial solution obtained
% from an other dimensionality reduction technique may be specified in
% initial_solution. The perplexity of the Gaussian kernel that is employed
% can be specified through perplexity (default = 30). The labels of the
% data are not used by t-SNE itself, however, they are used to color
% intermediate plots. Please provide an empty labels matrix [] if you
% don't want to plot results during the optimization.
% The low-dimensional data representation is returned in mappedX.
%
%
% (C) Laurens van der Maaten, 2010
% University of California, San Diego
if ~exist('labels', 'var')
labels = [];
end
if ~exist('no_dims', 'var') || isempty(no_dims)
no_dims = 2;
end
if ~exist('initial_dims', 'var') || isempty(initial_dims)
initial_dims = min(50, size(X, 2));
end
if ~exist('perplexity', 'var') || isempty(perplexity)
perplexity = 30;
end
% First check whether we already have an initial solution
if numel(no_dims) > 1
initial_solution = true;
ydata = no_dims;
no_dims = size(ydata, 2);
perplexity = initial_dims;
else
initial_solution = false;
end
% Normalize input data
X = X - min(X(:));
X = X / max(X(:));
X = bsxfun(@minus, X, mean(X, 1));
% Perform preprocessing using PCA
if ~initial_solution
disp('Preprocessing data using PCA...');
if size(X, 2) < size(X, 1)
C = X' * X;
else
C = (1 / size(X, 1)) * (X * X');
end
[M, lambda] = eig(C);
[lambda, ind] = sort(diag(lambda), 'descend');
M = M(:,ind(1:initial_dims));
lambda = lambda(1:initial_dims);
if ~(size(X, 2) < size(X, 1))
M = bsxfun(@times, X' * M, (1 ./ sqrt(size(X, 1) .* lambda))');
end
X = bsxfun(@minus, X, mean(X, 1)) * M;
clear M lambda ind
end
% Compute pairwise distance matrix
sum_X = sum(X .^ 2, 2);
D = bsxfun(@plus, sum_X, bsxfun(@plus, sum_X', -2 * (X * X')));
% Compute joint probabilities
P = d2p(D, perplexity, 1e-5); % compute affinities using fixed perplexity
clear D
% Run t-SNE
if initial_solution
ydata = tsne_p(P, labels, ydata);
else
ydata = tsne_p(P, labels, no_dims);
end
I am trying to understand this code but I cannot understand the part where the error occurs.
if size(X, 2) < size(X, 1)
C = X' * X;
else
C = (1 / size(X, 1)) * (X * X');
end
Why this condition is needed? Since the size of 'X' is (162x640), the else statement will be executed. I guess this is the problem. In the else statement, the size of 'C' will be (162x162). However, in the next line
M = M(:,ind(1:initial_dims));
the 'initial_dims' which equals to 640 is used. Did I used this code in a wrong way? Or is it just not available to the data set I use?
