My training data comes in batches. Sometimes, new batches (completely new samples) come with new columns that are not in old batches, or they may be missing some of the old columns.
For example, suppose there are two ingestions. In the 1st ingestion, we have ETL on a set of fields. In the 2nd ingestion, we have added a new field and we are not allowed to ingest and update the old records again (they may have been deleted for good).
Ideally, I want to train a classifier using all batches of data. What kind of algorithms would perform well under this scenario.