Nuist-Lee

Same problem occurred on me but MATLAB libsvm

What I got is the same ! I always get the same prediction value, even if I've already changed the inputdata. Specifically, I used 9 precipitation factors and real precipitation...

This is the code for trainning. ``` clear all load ("predictionfactors.mat"); [tsx,TSXps]=mapminmax(InputdataS1'); [ts,TSps]=mapminmax(JHy'); TSX=tsx'; TS=ts'; %% 选择回归预测分析最佳的SVM参数c&g [bestmse,bestc,bestg] = gaSVMcgForRegress(TS,TSX); % 打印选择结果 disp('打印选择结果'); str = sprintf( 'Best Cross Validation MSE...

In addition , @kevin031060 said he met the same issue when using Java interface ,and Python/Matlab is fine.While mine is using Matlab toolbox.

  TSX is prediction factors which are already transposed and normalizd and transposed again to be a 60*1 matrix. TS is real precipitation data, operated as above. It's a...

I mean 60x1 and 60x9

问题解决了！谢谢林老师的耐心指导！ Issue solved!!! Thanks for your patient help!!! The key is Y, which is the real precipitation data in my code named TS. In fact , I have 3 precipitation...