How to classify imbalanced data in weka?
There are a couple of things that you could try. 

Use Boosting (AdaBoostM1) so that the misclassified instances will be given extra weight.
Use weka.classifiers.meta.CostSensitiveClassifier    and give the "bad" instances a higher weight than the "good" instances.   Note: This will probably reduce your overall accuracy, but make your classifier do a better job of identifying the "bad" instances.
I have an imbalanced training data and i am using logistic regression in weka to classify.

There are two classes good and bad. Good has 75000 instances and bad
  3000.  My test data has 10000 good data.

When i train it is more inclined to good data i.e it classifies almost all bad instances good. What should i do ?
I tried to have 10000 good instances in training data instead of 75000 but still the problem is same.