I have a large data set of about 1.8 million rows with 80 variables. I would like to find a good technique (code or package) in R that can reduce the amount of training data without damaging the representation of the original data too much. I'm going to use this data set for two purposes:
- Predicting a binary outcome ( rows that have "true" as a value are only 1.5% of the data).
- Predicting a continuous variable.
Any Idea what technique in R can help with this issue?