How can I hot one encode in Matlab? [duplicate]

问题:

This question already has an answer here:

• Create a zero-filled 2D array with ones at positions indexed by a vector 4 answers

Often you are given a vector of integer values representing your labels (aka classes), for example

[2; 1; 3; 3; 2]

and you would like to hot one encode this vector, such that each value is represented by a 1 in the column indicated by the value in each row of the labels vector, for example

[0 1 0;  1 0 0;  0 0 1;  0 0 1;  0 1 0]

回答1:

For speed and memory savings, you can use bsxfun combined with eq to accomplish the same thing. While your eye solution may work, your memory usage grows quadratically with the number of unique values in X.

Y = bsxfun(@eq, X(:), 1:max(X));

Or as an anonymous function if you prefer:

hotone = @(X)bsxfun(@eq, X(:), 1:max(X));

Or if you're on Octave (or MATLAB version R2016b and later) , you can take advantage of automatic broadcasting and simply do the following as suggested by @Tasos.

Y = X == 1:max(X);

Benchmark

Here is a quick benchmark showing the performance of the various answers with varying number of elements on X and varying number of unique values in X.

function benchit()      nUnique = round(linspace(10, 1000, 10));     nElements = round(linspace(10, 1000, 12));      times1 = zeros(numel(nUnique), numel(nElements));     times2 = zeros(numel(nUnique), numel(nElements));     times3 = zeros(numel(nUnique), numel(nElements));     times4 = zeros(numel(nUnique), numel(nElements));     times5 = zeros(numel(nUnique), numel(nElements));      for m = 1:numel(nUnique)         for n = 1:numel(nElements)             X = randi(nUnique(m), nElements(n), 1);             times1(m,n) = timeit(@()bsxfunApproach(X));              X = randi(nUnique(m), nElements(n), 1);             times2(m,n) = timeit(@()eyeApproach(X));              X = randi(nUnique(m), nElements(n), 1);             times3(m,n) = timeit(@()sub2indApproach(X));              X = randi(nUnique(m), nElements(n), 1);             times4(m,n) = timeit(@()sparseApproach(X));              X = randi(nUnique(m), nElements(n), 1);             times5(m,n) = timeit(@()sparseFullApproach(X));         end     end      colors = get(0, 'defaultaxescolororder');      figure;      surf(nElements, nUnique, times1 * 1000, 'FaceColor', colors(1,:), 'FaceAlpha', 0.5);     hold on     surf(nElements, nUnique, times2 * 1000, 'FaceColor', colors(