A global LightGBM with a station-ID feature generally beats cluster-level and per-station models for probabilistic hourly bike-share demand forecasting.
Model-based clustering with Hidden Markov Model regression for time series with regime changes
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Comparative Analysis of Global and Local Probabilistic Time Series Forecasting for Contiguous Spatial Demand Regions
A global LightGBM with a station-ID feature generally beats cluster-level and per-station models for probabilistic hourly bike-share demand forecasting.