Hello - Has anyone ever played with ML models for forecasting?
Google has TimesFM -- https://github.com/google-research/timesfm -- which is a time series forecasting model that is designed to do predictions with far fewer inputs. (It's pre-trained on *lots* of time series data, so taking a smaller sample of data it can forecast from there.) Potential use cases -- no idea how well it'd work: - Scoring an anomaly score for each transaction -- how much is this away from the predicted normal of a transaction. - Forecasting transactions for the next three months, six months, or further -- what is the trend line? This could be based on only the previous few months or a longer term history. Mark -- You received this message because you are subscribed to the Google Groups "Beancount" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion visit https://groups.google.com/d/msgid/beancount/9000f5f3-865e-4cfe-b2df-ef8ef36cff61n%40googlegroups.com.
