SVM Classification with Caret Error (Basic)

You have 10 different classes and yet you are only including 10 cases in train(). This means that when you resample you will frequently not have all 10 classes in individual instances of your classifier. train() is having difficulty combining the results of these varying-category SVMs.

You can fix this by some combination of increasing the number of cases, decreasing the number of classes, or even using a different classifier.