CoInfoSim is a research simulator for evaluating predictive cooperation across attribute subsets in supervised classification.
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Occupancy Detection
DOI: 10.24432/C5X01N
License: CC BY 4.0 (license text)
Creative Commons Attribution 4.0 International. Attribution required.
Source: https://archive.ics.uci.edu/dataset/357/occupancy+detection
Candanedo, L. (2016). Occupancy Detection [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5X01N
- datatraining.txt sha256:b2c4d0ce2b9e4e453c476f7125ef31aeec2d1f5c7f5572d0e80de3df6521ab56 (596,674 bytes)
- datatest.txt sha256:1b92c7c1b2838963464fa891a610cf3c5db4becb7189189b29b330107a584c7f (200,766 bytes)
- datatest2.txt sha256:d026d1bd5aeccd4aff4f3b3710d48e40613bd5fc370db7e61bbdcaa50d985095 (699,664 bytes)
Air Quality
DOI: 10.24432/C59K5F
License: CC BY 4.0 (license text)
UCI displays this dataset as CC BY 4.0. Data are intended for research use; please cite the associated publication (De Vito et al., Sensors and Actuators B: Chemical, 2008).
Source: https://archive.ics.uci.edu/dataset/360/air+quality
De Vito, S. (2016). Air Quality [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C59K5F
- AirQualityUCI.csv sha256:13277ae5d8581e80b7be09d47c7d3d06fe9b8e957078f2cf6e859f955e62f996 (785,065 bytes)
SUPPORT2
DOI: 10.3886/ICPSR02957.v2
License: No explicit redistribution license identified; public research dataset; source acknowledgment required
No explicit redistribution license was identified for SUPPORT2. It is a public research dataset; follow the acknowledgment policy of the original HBiostat dataset site when using this file.
Source: https://hbiostat.org/data/
Knaus WA, et al. The SUPPORT Prognostic Model. Vanderbilt University Department of Biostatistics (HBiostat). https://doi.org/10.3886/ICPSR02957.v2
- support2.csv sha256:79621945edf2a5c8dc36359684ff356d3c6025e773ba4fefac26f865f7894c78 (3,141,732 bytes)
Occupancy Detection Baseline (fast)
Dataset: Occupancy Detection
Does training on single-Gaussian synthetic data preserve the cooperative advantages observed when classifiers are evaluated on real Occupancy data? Equivalently: which training distribution best preserves the cooperative structure observed under real-data evaluation in the Occupancy Detection dataset?
scenarios/000001_occupancy_baseline_fast/occupancy_baseline_scenario_report_fast_000001.html
Machine-readable: semantic manifest · provenance (JSON-LD)
Open scenario report
Occupancy Detection Baseline (full)
Dataset: Occupancy Detection
Does training on single-Gaussian synthetic data preserve the cooperative advantages observed when classifiers are evaluated on real Occupancy data? Equivalently: which training distribution best preserves the cooperative structure observed under real-data evaluation in the Occupancy Detection dataset?
scenarios/000002_occupancy_baseline_full/occupancy_baseline_scenario_report_full_000002.html
Machine-readable: semantic manifest · provenance (JSON-LD)
Open scenario report
Occupancy Detection Baseline (smoke)
Dataset: Occupancy Detection
Does training on single-Gaussian synthetic data preserve the cooperative advantages observed when classifiers are evaluated on real Occupancy data? Equivalently: which training distribution best preserves the cooperative structure observed under real-data evaluation in the Occupancy Detection dataset?
scenarios/000000_occupancy_baseline_smoke/occupancy_baseline_scenario_report_smoke_000000.html
Machine-readable: semantic manifest · provenance (JSON-LD)
Open scenario report
SUPPORT2 180-Day Mortality Baseline (full)
Dataset: SUPPORT2
To what extent do class-conditional Single Gaussian and GMM synthetic training distributions preserve the cooperative channel-subset structure observed for 180-day mortality prediction on a fixed real SUPPORT2 test set?
scenarios/000007_support2_baseline_full/support2_scenario_report_full_000007.html
Machine-readable: semantic manifest · provenance (JSON-LD)
Open scenario report
SUPPORT2 180-Day Mortality Baseline (full)
Dataset: SUPPORT2
To what extent do class-conditional Single Gaussian and GMM synthetic training distributions preserve the cooperative channel-subset structure observed for 180-day mortality prediction on a fixed real SUPPORT2 test set?
scenarios/000008_support2_baseline_full/support2_scenario_report_full_000008.html
Machine-readable: semantic manifest · provenance (JSON-LD)
Open scenario report
UCI Air Quality Baseline (full)
Dataset: UCI Air Quality
To what extent do single-Gaussian and class-conditional GMM synthetic training distributions preserve the cooperative channel structure observed when classifiers detect elevated benzene concentration on a fixed future real-data evaluation period?
scenarios/000005_air_quality_baseline_full/air_quality_scenario_report_full_000005.html
Machine-readable: semantic manifest · provenance (JSON-LD)
Open scenario report
UCI Air Quality Baseline (full-scale)
Dataset: UCI Air Quality
To what extent do single-Gaussian and class-conditional GMM synthetic training distributions preserve the cooperative channel structure observed when classifiers detect elevated benzene concentration on a fixed future real-data evaluation period?
scenarios/000006_air_quality_baseline_full-scale/air_quality_scenario_report_full-scale_000006.html
Machine-readable: semantic manifest · provenance (JSON-LD)
Open scenario report
UCI Air Quality Baseline (smoke)
Dataset: UCI Air Quality
To what extent do single-Gaussian and class-conditional GMM synthetic training distributions preserve the cooperative channel structure observed when classifiers detect elevated benzene concentration on a fixed future real-data evaluation period?
scenarios/000003_air_quality_baseline_smoke/air_quality_scenario_report_smoke_000003.html
Machine-readable: semantic manifest · provenance (JSON-LD)
Open scenario report
UCI Air Quality Baseline (smoke)
Dataset: UCI Air Quality
To what extent do single-Gaussian and class-conditional GMM synthetic training distributions preserve the cooperative channel structure observed when classifiers detect elevated benzene concentration on a fixed future real-data evaluation period?
scenarios/000004_air_quality_baseline_smoke/air_quality_scenario_report_smoke_000004.html
Machine-readable: semantic manifest · provenance (JSON-LD)
Open scenario report
See the project repository for the CoInfoSim citation file and license. Dataset citations and license/acknowledgment status are listed with each dataset above; SUPPORT2 in particular carries no open redistribution license and requires source acknowledgment rather than attribution under an open license.