Python: sklearn svm，提供自定义丢失函数

The way I use sklearn's svm module now, is to use its defaults. However, its not doing particularly well for my dataset. Is it possible to provide a custom loss function , or a custom kernel? If so, what is the way to write such a function so that it matches with what sklearn's svm expects and how to pass such a function to the trainer? The way I use sklearn's svm module now, is to u