SVM prediction does not predict OK although the support vectors are valid

问题

I have a following(fig 1) unlabeled training set which I am trying to detect the outliers, have come up with a procedure to label the data with 0:normal data and 1:outlier and want to train it with SVM. I followed this instructions to train the SVM's model but when I am trying to predict the labels of same data I have trained the SVM it does not predict any(fig 2)!

fig 1: the support vectors after training

fig 2: the prediction of SVM model on the same data it has been training with

The output of prediction is not supposed to look like this! The code I have used for prediction is:

out = predict(model, data');

Question:

What is wrong with my approach?

回答1:

For what it worth, I have found the answer to my question and now its working fine.

The result of prediction after using a non-linear kernel, but I don't know why this happened?

来源：https://stackoverflow.com/questions/39267100/svm-prediction-does-not-predict-ok-although-the-support-vectors-are-valid