{ "data_id": "1504", "name": "steel-plates-fault", "exact_name": "steel-plates-fault", "version": 1, "version_label": null, "description": "**Author**: Semeion, Research Center of Sciences of Communication, Rome, Italy. \r\n**Source**: [UCI](http:\/\/archive.ics.uci.edu\/ml\/datasets\/steel+plates+faults) \r\n**Please cite**: Dataset provided by Semeion, Research Center of Sciences of Communication, Via Sersale 117, 00128, Rome, Italy. \r\n\r\n**Steel Plates Faults Data Set** \r\nA dataset of steel plates' faults, classified into 7 different types. The goal was to train machine learning for automatic pattern recognition.\r\n\r\nThe dataset consists of 27 features describing each fault (location, size, ...) and 7 binary features indicating the type of fault (on of 7: Pastry, Z_Scratch, K_Scatch, Stains, Dirtiness, Bumps, Other_Faults). The latter is commonly used as a binary classification target ('common' or 'other' fault.)\r\n\r\n### Attribute Information \r\n* V1: X_Minimum \r\n* V2: X_Maximum \r\n* V3: Y_Minimum \r\n* V4: Y_Maximum \r\n* V5: Pixels_Areas \r\n* V6: X_Perimeter \r\n* V7: Y_Perimeter \r\n* V8: Sum_of_Luminosity \r\n* V9: Minimum_of_Luminosity \r\n* V10: Maximum_of_Luminosity \r\n* V11: Length_of_Conveyer \r\n* V12: TypeOfSteel_A300 \r\n* V13: TypeOfSteel_A400 \r\n* V14: Steel_Plate_Thickness \r\n* V15: Edges_Index \r\n* V16: Empty_Index \r\n* V17: Square_Index \r\n* V18: Outside_X_Index \r\n* V19: Edges_X_Index \r\n* V20: Edges_Y_Index \r\n* V21: Outside_Global_Index \r\n* V22: LogOfAreas \r\n* V23: Log_X_Index \r\n* V24: Log_Y_Index \r\n* V25: Orientation_Index \r\n* V26: Luminosity_Index \r\n* V27: SigmoidOfAreas \r\n* V28: Pastry \r\n* V29: Z_Scratch \r\n* V30: K_Scatch \r\n* V31: Stains \r\n* V32: Dirtiness \r\n* V33: Bumps \r\n* Class: Other_Faults \r\n\r\n### Relevant Papers \r\n1.M Buscema, S Terzi, W Tastle, A New Meta-Classifier,in NAFIPS 2010, Toronto (CANADA),26-28 July 2010, 978-1-4244-7858-6\/10 \u00c2\u00a92010 IEEE \r\n2.M Buscema, MetaNet: The Theory of Independent Judges, in Substance Use & Misuse, 33(2), 439-461,1998 ", "format": "ARFF", "uploader": "Rafael G. 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The latter is commonly used as a binary classification target ('common' or 'other' fault.) ### Attribute Information * V1: X_Minimum * V2: X_Maxi " ], "weight": 5 }, "qualities": { "NumberOfInstances": 1941, "NumberOfFeatures": 34, "NumberOfClasses": 2, "NumberOfMissingValues": 0, "NumberOfInstancesWithMissingValues": 0, "NumberOfNumericFeatures": 33, "NumberOfSymbolicFeatures": 1, "MinKurtosisOfNumericAtts": -1.8563564132863728, "Quartile2MeansOfNumericAtts": 0.6105286450283357, "REPTreeDepth3AUC": 1, "DecisionStumpAUC": 0.649386428300233, "MaxAttributeEntropy": null, "MinMeansOfNumericAtts": -0.13130504894384337, "Quartile2MutualInformation": null, "REPTreeDepth3ErrRate": 0, "DecisionStumpErrRate": 0.3467284904688305, "MaxKurtosisOfNumericAtts": 1663.0518475718168, "MinMutualInformation": null, "Quartile2SkewnessOfNumericAtts": 0.8514222506284619, "REPTreeDepth3Kappa": 1, "DecisionStumpKappa": 0, "MaxMeansOfNumericAtts": 1650738.7053065428, "MinNominalAttDistinctValues": 2, 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