What does "subsampling at 5%" mean? This from the description of a kaggle competition:

Note that the negative class has been subsampled for this dataset at 5%, and thus receives a 20x weighting in the scoring metric.

They don't mention the metric used – I am guessing its accuracy, since it's a classification problem. But I don't understand the subsampling bit. In the training dataset provided, the 'negative' class comprises almost 25%. Are they saying in the 'population'/their database, it's 5%?

The note means that only 5%, or 1 in 20, of the negative transactions are presented, whereas the positive transactions are represented in full.
If the negative data weren't subsampled, there would be 25 times as many negative transactions, or about 8.5 million. We can conclude that the positive ratio (positive meaning a default on credit card payment) in the full data is about 1.6%.
