How to address class imbalance?

[chiragpr]

I am using my custom dataset with 2 classes which has 10% samples with label 1 and 90% samples with label 0 in both source and target datasets. The accuracy is quite good, and is around 98+%!. But, calling accuracy 'precision' is incorrect as precision means (no. of samples in target classified as 1)/(no. of samples in target with ground truth 1).
But, how to find precision in this case? Which part of the code must be modified to find the following:

1. sensitivity (precision) = (no. of samples in target classified as 1)/(no. of samples in target with ground truth 1).
2. specificity = (no. of samples in target classified as 0)/(no. of samples in target with ground truth 0).

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