IBM has a time-series model for every task
Pankaj Dayama; Vijay Ekambaram; Wesley Gifford; Lars Graf; Thomas Ortner; Angeliki Pantazi; Chandra Reddy; Roman Vaculin
Time-series data comes in many forms, and with many potential applications. That means no single forecasting method can work best all the time.
If you’re trying to predict tomorrow’s high and low temperature, or whether a company will hit next week’s sales target, point forecasting is a good bet. But if you’re trying to decide when to restock a product or evaluate a company’s risk exposure, a probabilistic forecast could be more useful. Other times, you may be trying to detect anomalies in a...