Linear regression

By Xiaogang Su, Xin Yan, C. Tsai. 2012

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BIN-CT: Urban Waste Collection based in Predicting the Container Fill Level (2018, methodology): “The algorithms used in this comparison are the following: Linear Regression (Su et al., 2012), Gaussian processes (Mackay, 1998) and Support Vector Machine for regression (SMOreg) (Rivas-Perea, 2013).”
HeatPrompt: Zero-Shot Vision-Language Modeling of Urban Heat Demand from Satellite Images (2026, unknown): “Model R 2 (± std) MAE (± std) % R 2 Baseline simulation 0.32 ± 0.30 287.1 ± 56.4 – Linear Regression [28] 0.43 ± 0.15 244.7 ± 39.3 +34.4% Ridge Regression [29] 0.47 ± 0.15 240.9 ± 38.8 +46.9% Random Forest [30] 0.35 ± 0.12 238.1 ± 42.6 +8.6% HistGradBoost [31] 0.34 ± 0.41 237.8 ± 49.0 +6.3% MLP…”