Computer implemented systems for automatic hierarchy for large scale time …

This invention describes a computer system that automatically creates the best way to organize large amounts of time-stamped information for making predictions. Instead of relying on a pre-set structure, the system analyzes the data itself, identifies key characteristics, groups similar data points, and arranges them in an optimal order to improve forecasting accuracy. It can even intelligently sample the data first to make the process more efficient.

Why it matters: The significant advancements in automated machine learning (AutoML) and cloud-based data processing since 2019 make implementing and scaling such a system considerably more feasible and effective today. Algorithms for automatically optimizing data structures for forecasting have also matured, offering better performance.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedHeavy software system, data science algorithms.

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