How to do class balancing?
With such a heavy imbalance and two classes (it seems) you could treat this as more of an outlier detection problem. You should read up on models and algorithms in that direction!
If you go forward with a traditional classification you need to balance the data set, consider methods such as SMOTE.
Depending on the size of your data I would generally recommend downsampling the majority class which avoids producing &quot;synthetic&quot; cases but advanced methods such as SMOTE basically take care of this decision for you.
Can you elaborate what you mean with your first question as well? A classification algorithm needs 0/1 labels and therefore the output score cannot be ordered in the way that you mention. Some classification algorithms put out a probability score instead of predicted label so if this is what you mean I can tell you that the imbalance will still be a problem.