{ "data_id": "40496", "name": "LED-display-domain-7digit", "exact_name": "LED-display-domain-7digit", "version": 1, "version_label": "1", "description": "**Author**: Breiman,L., Friedman,J.H., Olshen,R.A., and Stone,C.J. \r\n**Source**: [UCI](http:\/\/archive.ics.uci.edu\/ml\/datasets\/LED+Display+Domain), [KEEL](http:\/\/sci2s.ugr.es\/keel\/dataset.php?cod=63, https:\/\/archive.ics.uci.edu\/ml\/datasets\/LED+Display+Domain) - 1988 \r\n**Please cite**: [UCI](https:\/\/archive.ics.uci.edu\/ml\/citation_policy.html) \r\n\r\n**LED display data set** \r\nThis simple domain contains 7 Boolean attributes and 10 classes, the set of decimal digits. Recall that LED displays contain 7 light-emitting diodes -- hence the reason for 7 attributes. The class attribute is an integer ranging between 0 and 9 inclusive, representing the possible digits show on the display.\r\n\r\nThe problem would be easy if not for the introduction of noise. In this case, each attribute value has the 10% probability of having its value inverted. \r\n\r\nIt's valuable to know the optimal Bayes rate for these databases. In this case, the misclassification rate is 26% (74% classification accuracy).\r\n \r\n### Attribute Information \r\n* V1-V7 represent each of the 7 LEDs, with values either 0 or 1, according to whether the corresponding light is on or not for the decimal digit. Each has a 10% percent chance of being inverted.", "format": "ARFF", "uploader": "Rafael Gomes Mantovani", "uploader_id": 64, "visibility": "public", "creator": null, "contributor": null, "date": "2016-07-29 20:36:10", "update_comment": null, "last_update": "2016-07-29 20:36:10", "licence": "Public", "status": "active", "error_message": null, "url": "https:\/\/www.openml.org\/data\/download\/4535757\/phpSj3fWL", "default_target_attribute": "Class", "row_id_attribute": null, "ignore_attribute": null, "runs": 13156, "suggest": { "input": [ "LED-display-domain-7digit", "This simple domain contains 7 Boolean attributes and 10 classes, the set of decimal digits. Recall that LED displays contain 7 light-emitting diodes -- hence the reason for 7 attributes. The class attribute is an integer ranging between 0 and 9 inclusive, representing the possible digits show on the display. The problem would be easy if not for the introduction of noise. In this case, each attribute value has the 10% probability of having its value inverted. It's valuable to know the optimal Bay " ], "weight": 5 }, "qualities": { "NumberOfInstances": 500, "NumberOfFeatures": 8, "NumberOfClasses": 10, "NumberOfMissingValues": 0, "NumberOfInstancesWithMissingValues": 0, "NumberOfNumericFeatures": 7, "NumberOfSymbolicFeatures": 1, "EquivalentNumberOfAtts": null, "MeanSkewnessOfNumericAtts": -0.7264117116188794, "Quartile2MeansOfNumericAtts": 0.67, "MajorityClassPercentage": 11.4, "MeanStdDevOfNumericAtts": 0.45729419529310666, "Quartile2MutualInformation": null, "MajorityClassSize": 57, "MinAttributeEntropy": null, "Quartile2SkewnessOfNumericAtts": -0.7252545765089368, "MaxAttributeEntropy": null, "MinKurtosisOfNumericAtts": -1.872759540452944, "PercentageOfBinaryFeatures": 0, "Quartile2StdDevOfNumericAtts": 0.4706836370348403, "MaxKurtosisOfNumericAtts": 0.7363180226323118, "MinMeansOfNumericAtts": 0.3960000000000001, "PercentageOfInstancesWithMissingValues": 0, "Quartile3AttributeEntropy": null, "MaxMeansOfNumericAtts": 0.818, "MinMutualInformation": null, "PercentageOfMissingValues": 0, "Quartile3KurtosisOfNumericAtts": -0.8749526989054361, "MaxMutualInformation": null, "MinNominalAttDistinctValues": 10, "PercentageOfNumericFeatures": 87.5, "Quartile3MeansOfNumericAtts": 0.734, "MaxNominalAttDistinctValues": 10, "MinSkewnessOfNumericAtts": -1.6532963313105244, "PercentageOfSymbolicFeatures": 12.5, "Quartile3MutualInformation": null, "MaxSkewnessOfNumericAtts": 0.4265826667894626, "MinStdDevOfNumericAtts": 0.386230952536685, "Quartile1AttributeEntropy": null, "Quartile3SkewnessOfNumericAtts": -0.36707981414182267, "MaxStdDevOfNumericAtts": 0.492325877381108, "MinorityClassPercentage": 7.3999999999999995, "Quartile1KurtosisOfNumericAtts": -1.8253446979076169, "Quartile3StdDevOfNumericAtts": 0.4895542121699178, "MeanAttributeEntropy": null, "MinorityClassSize": 37, "Quartile1MeansOfNumericAtts": 0.5900000000000001, "StdvNominalAttDistinctValues": 0, "MeanKurtosisOfNumericAtts": -1.1173581845410985, "NumberOfBinaryFeatures": 0, "Quartile1MutualInformation": null, "MeanMeansOfNumericAtts": 0.6565714285714286, "Quartile1SkewnessOfNumericAtts": -1.0623385393261326, "AutoCorrelation": 0.7214428857715431, "MeanMutualInformation": null, "Quartile1StdDevOfNumericAtts": 0.44230676067756874, "ClassEntropy": 3.312307702487186, "MeanNoiseToSignalRatio": null, "Quartile2AttributeEntropy": null, "Dimensionality": 0.016, "MeanNominalAttDistinctValues": 10, "Quartile2KurtosisOfNumericAtts": -1.4799416454808219 }, "tags": [ { "uploader": "2", "tag": "artificial" }, { "uploader": "2", "tag": "keel" }, { "uploader": "38960", "tag": "Machine Learning" }, { "uploader": "38960", "tag": "Meteorology" }, { "uploader": "348", "tag": "OpenML100" }, { "uploader": "3886", "tag": "study_123" }, { "uploader": "5824", "tag": "study_135" }, { "uploader": "1", "tag": "study_14" }, { "uploader": "64", "tag": "study_50" }, { "uploader": "64", "tag": "study_52" }, { "uploader": "3198", "tag": "study_76" }, { "uploader": "4209", "tag": "study_88" }, { "uploader": "2", "tag": "uci" } ], "features": [ { "name": "Class", "index": "7", "type": "nominal", "distinct": "10", "missing": "0", "target": "1", "distr": [ [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10" ], [ [ "45", "0", "0", "0", "0", "0", "0", "0", "0", "0" ], [ "0", "37", "0", "0", "0", "0", "0", "0", "0", "0" ], [ "0", "0", "51", "0", "0", "0", "0", "0", "0", "0" ], [ "0", "0", "0", "57", "0", "0", "0", "0", "0", "0" ], [ "0", "0", "0", "0", "52", "0", "0", "0", "0", "0" ], [ "0", "0", "0", "0", "0", "52", "0", "0", "0", "0" ], [ "0", "0", "0", "0", "0", "0", "47", "0", "0", "0" ], [ "0", "0", "0", "0", "0", "0", "0", "57", "0", "0" ], [ "0", "0", "0", "0", "0", "0", "0", "0", "53", "0" ], [ "0", "0", "0", "0", "0", "0", "0", "0", "0", "49" ] ] ] }, { "name": "V1", "index": "0", "type": "numeric", "distinct": "2", "missing": "0", "min": "0", "max": "1", "mean": "1", "stdev": "0" }, { "name": "V2", "index": "1", "type": "numeric", "distinct": "2", "missing": "0", "min": "0", "max": "1", "mean": "1", "stdev": "0" }, { "name": "V3", "index": "2", "type": "numeric", "distinct": "2", "missing": "0", "min": "0", "max": "1", "mean": "1", "stdev": "0" }, { "name": "V4", "index": "3", "type": "numeric", "distinct": "2", "missing": "0", "min": "0", "max": "1", "mean": "1", "stdev": "0" }, { "name": "V5", "index": "4", "type": "numeric", "distinct": "2", "missing": "0", "min": "0", "max": "1", "mean": "0", "stdev": "0" }, { "name": "V6", "index": "5", "type": "numeric", "distinct": "2", "missing": "0", "min": "0", "max": "1", "mean": "1", "stdev": "0" }, { "name": "V7", "index": "6", "type": "numeric", "distinct": "2", "missing": "0", "min": "0", "max": "1", "mean": "1", "stdev": "0" } ], "nr_of_issues": 0, "nr_of_downvotes": 0, "nr_of_likes": 0, "nr_of_downloads": 10, "total_downloads": 11, "reach": 10, "reuse": 17, "impact_of_reuse": 0, "reach_of_reuse": 4, "impact": 19 }