It really depends on your data but there are at least four things you could try:

- Upsample the training set by copying the examples in each category 
- Downsample the training set by deleting some examples from the dominating categories
- Use a boosting algorithm like [scikit-learn's Adaboost](http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.AdaBoostClassifier.html)
- Use cost-sensitive classification algorithm