MATLAB libsvm issue ：same result when predicting

[Nuist-Lee]

林老师您好！ I always get the same prediction value, even if I've already changed the inputdata. Specifically, I used 9 precipitation factors and real precipitation data from 1951 to 2010 to train the SVM regression model. Then I input the factors from 2011 to 2016 to the model in order to get the predicted precipitation data. But all I got was an array with the same 6 numberslike[248 248 248 248 248 248]. When I change the inputdata, the result may change but still an array with the same six numbers. Sometimes the result array can be 'almost' the same, like [222.121971040339 217.475177855453 221.321911068434 215.667836808570 222.829461145174]. It's also been found that only if I input the data that is very very closed to the trainnig data(1951-2010 factors), the result can be quite well. Ironically, when I use some classic dataset (from my reference books), the result will be pretty pretty good. Add on, RBF kernel was used. My version is MATLAB R2018a with libsvm-3.14.