Imbalanced dataset in MLP classifier in python
You can try using data re-sampling techniques. They can be divided in four categories: undersampling the majority class, oversampling the minority class, combining over and under sampling, and creating an ensemble of balanced datasets.

The above methods and more are implemented in the imbalanced-learn library in Python that interfaces with scikit-learn. See ipython notebook for an example.