# Quantile Regression on Scenario 1 (n=5000) Source: [Quantile Regression on Scenario 1 (n=5000)]() Collection index: [llms.txt]() Data updated: 2026-05-08T10:38:44.080Z Evaluation of model performance for Quantile Regression on the Scenario 1 dataset subset (N=5000), assessed using Mean Squared Error (MSE) across various quantiles (τ=0.05, 0.25, 0.5, 0.75, 0.95). A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. | Scope | Recorded value | | --- | --- | | Task | Quantile Regression | | Dataset (including any stated split) | Scenario 1 (n=5000) | | Metric | MSE (Quantile 0.05) | | Unit | SCALAR | | Direction | Lower is better | | Results loaded | 16 of 16 | | Coverage | All results currently returned for this benchmark | Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol. ## Metrics - [MSE (Quantile 0.05)](): Lower is better; unit: SCALAR. - [MSE (Quantile 0.25)](): Lower is better; unit: SCALAR. - [MSE (Quantile 0.5)](): Lower is better; unit: SCALAR. - [MSE (Quantile 0.75)](): Lower is better; unit: SCALAR. - [MSE (Quantile 0.95)](): Lower is better; unit: SCALAR. ## Recorded results | Method | MSE (Quantile 0.05) | Result date | Report paper | | --- | --- | --- | --- | | Baseline | 0.0996 | Not recorded | 69fd6e1f5497b3b670c894ba | | ConquerNet | 0.1006 | Not recorded | 69fd6e1f5497b3b670c894ba | | ConquerNet | 0.1033 | Not recorded | 69fd6e1f5497b3b670c894ba | | Baseline | 0.1051 | Not recorded | 69fd6e1f5497b3b670c894ba | | ConquerNet | 0.1079 | Not recorded | 69fd6e1f5497b3b670c894ba | | ConquerNet | 0.1115 | Not recorded | 69fd6e1f5497b3b670c894ba | | ConquerNet | 0.1124 | Not recorded | 69fd6e1f5497b3b670c894ba | | ConquerNet | 0.1139 | Not recorded | 69fd6e1f5497b3b670c894ba | | Baseline | 0.1143 | Not recorded | 69fd6e1f5497b3b670c894ba | | ConquerNet | 0.1149 | Not recorded | 69fd6e1f5497b3b670c894ba | | ConquerNet | 0.1172 | Not recorded | 69fd6e1f5497b3b670c894ba | | ConquerNet | 0.124 | Not recorded | 69fd6e1f5497b3b670c894ba | | Baseline | 0.1249 | Not recorded | 69fd6e1f5497b3b670c894ba | | ConquerNet | 0.1251 | Not recorded | 69fd6e1f5497b3b670c894ba | | ConquerNet | 0.1272 | Not recorded | 69fd6e1f5497b3b670c894ba | | ConquerNet | 0.136 | Not recorded | 69fd6e1f5497b3b670c894ba | ### Baseline MSE (Quantile 0.05): 0.0996. Result ID: 69fdbd2a47f34ce924e16584. [Reporting paper]() Recorded evaluation configuration: {"Model":"Model A"}. This record does not assert independent reproduction. ### ConquerNet MSE (Quantile 0.05): 0.1006. Result ID: 69fdbd2a47f34ce924e16535. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"Model A","Kernel":"Gaussian"}. This record does not assert independent reproduction. ### ConquerNet MSE (Quantile 0.05): 0.1033. Result ID: 69fdbd2a47f34ce924e1658a. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"Model B","Smoothing Kernel":"Uniform"}. This record does not assert independent reproduction. ### Baseline MSE (Quantile 0.05): 0.1051. Result ID: 69fdbd2a47f34ce924e16534. [Reporting paper]() Recorded evaluation configuration: {"Model":"Model A"}. This record does not assert independent reproduction. ### ConquerNet MSE (Quantile 0.05): 0.1079. Result ID: 69fdbd2a47f34ce924e16586. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"Model A","Smoothing Kernel":"Uniform"}. This record does not assert independent reproduction. ### ConquerNet MSE (Quantile 0.05): 0.1115. Result ID: 69fdbd2a47f34ce924e1658b. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"Model B","Smoothing Kernel":"Epanechnikov"}. This record does not assert independent reproduction. ### ConquerNet MSE (Quantile 0.05): 0.1124. Result ID: 69fdbd2a47f34ce924e16585. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"Model A","Smoothing Kernel":"Gaussian"}. This record does not assert independent reproduction. ### ConquerNet MSE (Quantile 0.05): 0.1139. Result ID: 69fdbd2a47f34ce924e16536. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"Model A","Kernel":"Uniform"}. This record does not assert independent reproduction. ### Baseline MSE (Quantile 0.05): 0.1143. Result ID: 69fdbd2a47f34ce924e16588. [Reporting paper]() Recorded evaluation configuration: {"Model":"Model B"}. This record does not assert independent reproduction. ### ConquerNet MSE (Quantile 0.05): 0.1149. Result ID: 69fdbd2a47f34ce924e16537. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"Model A","Kernel":"Epanechnikov"}. This record does not assert independent reproduction. ### ConquerNet MSE (Quantile 0.05): 0.1172. Result ID: 69fdbd2a47f34ce924e16589. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"Model B","Smoothing Kernel":"Gaussian"}. This record does not assert independent reproduction. ### ConquerNet MSE (Quantile 0.05): 0.124. Result ID: 69fdbd2a47f34ce924e1653a. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"Model B","Kernel":"Uniform"}. This record does not assert independent reproduction. ### Baseline MSE (Quantile 0.05): 0.1249. Result ID: 69fdbd2a47f34ce924e16538. [Reporting paper]() Recorded evaluation configuration: {"Model":"Model B"}. This record does not assert independent reproduction. ### ConquerNet MSE (Quantile 0.05): 0.1251. Result ID: 69fdbd2a47f34ce924e16587. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"Model A","Smoothing Kernel":"Epanechnikov"}. This record does not assert independent reproduction. ### ConquerNet MSE (Quantile 0.05): 0.1272. Result ID: 69fdbd2a47f34ce924e1653b. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"Model B","Kernel":"Epanechnikov"}. This record does not assert independent reproduction. ### ConquerNet MSE (Quantile 0.05): 0.136. Result ID: 69fdbd2a47f34ce924e16539. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"Model B","Kernel":"Gaussian"}. 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