The pooled covariance matrix of TRAINING must be positive definite.

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sun rise 2022-1-21

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1633570-the-pooled-covariance-matrix-of-training-must-be-positive-definite

评论： sun rise 2022-1-29

clc
clear all
load featurs_T
load featurs_S
load Group_Train
load Group_Test
cv_x=cov(Feat1);
[V,D] = eig(cv_x);
d=diag(D);
d=d(end:-1:1);
sm_d=cumsum(d) /sum(d);
idx=find(sm_d>0.99);
T=[V(:,end:-1:idx(1))]';
new_feat1=T*Feat1';
%TrainingSet= new_feat1';
new_feat2=T*Feat2';
%TestSet= new_feat2';
TrainingSet = new_feat1'; 
TestSet = new_feat2';
Group_Train1 = Group_Train1';
Group_Test1 = Group_Test1';
%------------------------
% result1= multisvm(TrainingSet,Group_Train1,TestSet,Group_Test1);
result1= classify(TestSet,TrainingSet,Group_Train1,'linear');
testresult = result1;
Accuracy = mean(Group_Test1==result) * 100;
fprintf('Accuracy = %.2f\n', Accuracy);
fprintf('error rate = %.2f\n ', mean(result ~= Group_Test1 ) * 100);

Error using classify (line 233)

The pooled covariance matrix of TRAINING must be positive definite.

Error in HOG2 (line 31)

result1= classify(TestSet,TrainingSet,Group_Train1,'linear');

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sun rise 2022-1-24

I actually used pca to reduce dimensions. But the error is still there

sun rise 2022-1-29

在 MATLAB Online 中打开

Feat1 = pca(Feat1);
Feat2 = pca (Feat2);

But why is pca decreasing the number of images and thus I get this error

The length of GROUP must equal the number of rows in TRAINING.

This is evident in the workspace

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采纳的回答

Matt J 2022-1-23

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1633570-the-pooled-covariance-matrix-of-training-must-be-positive-definite#answer_880015

I suggest you calculate the pooled covariance matrix and verify whether the error message is accurate.

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sun rise 2022-1-29

https://www.mathworks.com/matlabcentral/answers/1633570-the-pooled-covariance-matrix-of-training-must-be-positive-definite#comment_1961110

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