MATLAB - knnclassify 的用法

Question

做的时候:

load training.mat
training = G

load testing.mat
test = G

然后:

>> knnclassify(test.Inp, training.Inp, training.Ltr)

??? Error using ==> knnclassify at 91
The length of GROUP must equal the number of rows in TRAINING.

自:

>> size(training.Inp)
ans =
          40          40        2016

还有:

>> length(training.Ltr)
ans =
        2016

如何为 knnclassify(训练)training.inp 3-D 矩阵提供第二个参数，以便行数为 2016(第三维)？

Answer 1

假设您的 3D 数据被解释为 2016 年每个实例(第三维)的 40×40 特征矩阵，我们将不得不将其重新排列为大小为 2016×1600 的矩阵(行是样本，列是尺寸):

%# random data instead of the `load data.mat`
testing = rand(40,40,200);
training = rand(40,40,2016);
labels = randi(3, [2016 1]);     %# a class label for each training instance
                                 %# (out of 3 possible classes)

%# arrange data as a matrix whose rows are the instances,
%# and columns are the features
training = reshape(training, [40*40 2016])';
testing = reshape(testing, [40*40 200])';

%# k-nearest neighbor classification
prediction = knnclassify(testing, training, labels);