{ "data_id": "44145", "name": "sulfur", "exact_name": "sulfur", "version": 4, "version_label": "1", "description": "Dataset used in the tabular data benchmark https:\/\/github.com\/LeoGrin\/tabular-benchmark, transformed in the same way. This dataset belongs to the \"regression on numerical features\" benchmark. Original description: \n \n"The sulfur recovery unit (SRU) removes environmental pollutants from acid gas\nstreams before they are released into the atmosphere. Furthermore, elemental sulfur\nis recovered as a valuable by-product."\n\n5 inputs variables are gas and air flows.\n2 outputs to predict are H2S and SO2 concentrations\n\nSee Appendix A.5 of Fortuna, L., Graziani, S., Rizzo, A., Xibilia, M.G. "Soft Sensors for Monitoring and Control of Industrial Processes" (Springer 2007) for more info.", "format": "arff", "uploader": "Leo Grin", "uploader_id": 26324, "visibility": "public", "creator": "\"Fortuna\",\"L.\",\"Graziani\",\"S.\",\"Rizzo\",\"A.\",\"Xibilia\",\"M.G.\"", "contributor": "\"Leo Grin\"", "date": "2022-07-05 20:52:57", "update_comment": null, "last_update": "2022-07-05 20:52:57", "licence": "Public", "status": "active", "error_message": null, "url": "https:\/\/api.openml.org\/data\/download\/22103270\/dataset", "default_target_attribute": "y1", "row_id_attribute": null, "ignore_attribute": null, "runs": 0, "suggest": { "input": [ "sulfur", "Dataset used in the tabular data benchmark https:\/\/github.com\/LeoGrin\/tabular-benchmark, transformed in the same way. This dataset belongs to the \"regression on numerical features\" benchmark. Original description: "The sulfur recovery unit (SRU) removes environmental pollutants from acid gas streams before they are released into the atmosphere. Furthermore, elemental sulfur is recovered as a valuable by-product." 5 inputs variables are gas and air flows. 2 outputs to predict are H2S an " ], "weight": 5 }, "qualities": { "NumberOfInstances": 10081, "NumberOfFeatures": 7, "NumberOfClasses": 0, "NumberOfMissingValues": 0, "NumberOfInstancesWithMissingValues": 0, "NumberOfNumericFeatures": 7, "NumberOfSymbolicFeatures": 0, "PercentageOfMissingValues": 0, "AutoCorrelation": 0.9946381794642857, "PercentageOfNumericFeatures": 100, "Dimensionality": 0.0006943755579803591, "MajorityClassPercentage": null, "PercentageOfSymbolicFeatures": 0, "MajorityClassSize": null, "MinorityClassPercentage": null, "MinorityClassSize": null, "NumberOfBinaryFeatures": 0, "PercentageOfBinaryFeatures": 0, "PercentageOfInstancesWithMissingValues": 0 }, "tags": [ { "uploader": "38960", "tag": "Computer Systems" }, { "uploader": "38960", "tag": "Machine Learning" } ], "features": [ { "name": "y1", "index": "6", "type": "numeric", "distinct": "9368", "missing": "0", "target": "1", "min": "0", "max": "1", "mean": "0", "stdev": "0" }, { "name": "a1", "index": "0", "type": "numeric", "distinct": "9568", "missing": "0", "min": "0", "max": "1", "mean": "1", "stdev": "0" }, { "name": "a2", "index": "1", "type": "numeric", "distinct": "8249", "missing": "0", "min": "0", "max": "1", "mean": "1", "stdev": "0" }, { "name": "a3", "index": "2", "type": "numeric", "distinct": "9839", "missing": "0", "min": "0", "max": "1", "mean": "0", "stdev": "0" }, { "name": "a4", "index": "3", "type": "numeric", "distinct": "7561", "missing": "0", "min": "0", "max": "1", "mean": "1", "stdev": "0" }, { "name": "a5", "index": "4", "type": "numeric", "distinct": "6923", "missing": "0", "min": "0", "max": "1", "mean": "1", "stdev": "0" }, { "name": "y2", "index": "5", "type": "numeric", "distinct": "9678", "missing": "0", "min": "0", "max": "1", "mean": "0", "stdev": "0" } ], "nr_of_issues": 0, "nr_of_downvotes": 0, "nr_of_likes": 0, "nr_of_downloads": 0, "total_downloads": 0, "reach": 0, "reuse": 0, "impact_of_reuse": 0, "reach_of_reuse": 0, "impact": 0 }