{ "data_id": "41919", "name": "CPMP-2015-runtime-classification", "exact_name": "CPMP-2015-runtime-classification", "version": 1, "version_label": null, "description": "source: An Algorithm Selection Benchmark for the Container Pre-Marshalling Problem (CPMP)\nauthors: K. Tierney and Y. Malitsky (features) \/ K. Tierney and D. Pacino and S. Voss (algorithms)\ntranslator in coseal format: K. Tierney\n\nThis is an extension of the 2013 premarshalling dataset that includes more features and a set of test instances. \n\nThere are three sets of features:\n\nfeature_values.arff contains the full set of features from iteration 2 of our latent feature analysis (LFA) process (see paper)\nfeature_values_itr1.arff contains only the features after iteration 1 of LFA\nfeature_values_orig.arff containers the features used in PREMARHSALLING-ASTAR-2013\n\nWe also provide test data with an identical naming scheme (see _test). \n\nThe features for the pre-marshalling problem are all extremely easy and fast to\ncompute, thus the feature_costs.arff file has been omitted, as it would be time\n0 for every feature (regardless of using original, iteration 1 or iteration 2\nfeatures).\n\nThe feature computation code is available at https:\/\/bitbucket.org\/eusorpb\/cpmp-as\n\nNote: previously the scenario was called PREMARSHALLING-ASTAR-2015. To save same space, we renamed the scenario.", "format": "ARFF", "uploader": "Martin Hoang", "uploader_id": 8316, "visibility": "public", "creator": null, "contributor": null, "date": "2019-06-19 12:34:25", "update_comment": null, "last_update": "2019-06-19 12:34:25", "licence": "Public", "status": "active", "error_message": null, "url": "https:\/\/www.openml.org\/data\/download\/21378712\/file248cdf4cb6.arff", "kaggle_url": null, "default_target_attribute": "algorithm", "row_id_attribute": "row_id", "ignore_attribute": null, "runs": 14, "suggest": { "input": [ "CPMP-2015-runtime-classification", "source: An Algorithm Selection Benchmark for the Container Pre-Marshalling Problem (CPMP) authors: K. Tierney and Y. Malitsky (features) \/ K. Tierney and D. Pacino and S. Voss (algorithms) translator in coseal format: K. Tierney This is an extension of the 2013 premarshalling dataset that includes more features and a set of test instances. There are three sets of features: feature_values.arff contains the full set of features from iteration 2 of our latent feature analysis (LFA) process (see pap " ], "weight": 5 }, "qualities": { "NumberOfInstances": 527, "NumberOfFeatures": 23, "NumberOfClasses": 4, "NumberOfMissingValues": 0, "NumberOfInstancesWithMissingValues": 0, "NumberOfNumericFeatures": 22, "NumberOfSymbolicFeatures": 1, "MaxSkewnessOfNumericAtts": 1.8160639830700218, "MinStdDevOfNumericAtts": 0.05293820227455466, "Quartile1AttributeEntropy": null, "Quartile3SkewnessOfNumericAtts": 0.75104081803165, "MaxStdDevOfNumericAtts": 13.81073005054825, "MinorityClassPercentage": 14.800759013282732, "Quartile1KurtosisOfNumericAtts": -0.9471119401151773, "Quartile3StdDevOfNumericAtts": 2.1329005165383497, "MeanAttributeEntropy": null, "MinorityClassSize": 78, "Quartile1MeansOfNumericAtts": 0.4538575891840607, "StdvNominalAttDistinctValues": 0, "MeanKurtosisOfNumericAtts": 0.03566388250471597, "NumberOfBinaryFeatures": 0, "Quartile1MutualInformation": null, "MeanMeansOfNumericAtts": 4.069849398463, "Quartile1SkewnessOfNumericAtts": 0.12134019990103784, "MeanMutualInformation": null, "Quartile1StdDevOfNumericAtts": 0.1321994865931491, "AutoCorrelation": 0.4543726235741445, "MeanNoiseToSignalRatio": null, "Quartile2AttributeEntropy": null, "ClassEntropy": 1.8800596155195604, "MeanNominalAttDistinctValues": 4, "Quartile2KurtosisOfNumericAtts": -0.23354201346695502, "Dimensionality": 0.04364326375711575, "MeanSkewnessOfNumericAtts": 0.46249255607903555, "Quartile2MeansOfNumericAtts": 0.7936534895635671, "EquivalentNumberOfAtts": null, "MajorityClassPercentage": 39.46869070208729, "MeanStdDevOfNumericAtts": 1.8089946009351126, "Quartile2MutualInformation": null, "MajorityClassSize": 208, "MinAttributeEntropy": null, "Quartile2SkewnessOfNumericAtts": 0.5899631220617713, "MaxAttributeEntropy": null, "MinKurtosisOfNumericAtts": -2.006920996435009, "PercentageOfBinaryFeatures": 0, "Quartile2StdDevOfNumericAtts": 0.4896066105882946, "MaxKurtosisOfNumericAtts": 6.123205264379703, "MinMeansOfNumericAtts": 0.06597881043643254, "PercentageOfInstancesWithMissingValues": 0, "Quartile3AttributeEntropy": null, "MaxMeansOfNumericAtts": 30.20303605313095, "MinMutualInformation": null, "PercentageOfMissingValues": 0, "Quartile3KurtosisOfNumericAtts": 0.43206729665440835, "MaxMutualInformation": null, "MinNominalAttDistinctValues": 4, "PercentageOfNumericFeatures": 95.65217391304348, "Quartile3MeansOfNumericAtts": 4.761845927419355, "MaxNominalAttDistinctValues": 4, "MinSkewnessOfNumericAtts": -1.681204032266375, "PercentageOfSymbolicFeatures": 4.3478260869565215, "Quartile3MutualInformation": null }, "tags": [ { "uploader": "8316", "tag": "Algorithm Selection" }, { "uploader": "38960", "tag": "Artificial Intelligence" }, { "uploader": "38960", "tag": "Data Science" }, { "uploader": "38960", "tag": "Machine Learning" }, { "uploader": "38960", "tag": "Optimization" }, { "uploader": "8316", "tag": "R" } ], "features": [ { "name": "algorithm", "index": "22", "type": "nominal", "distinct": "4", "missing": "0", "target": "1", "distr": [ [ "astar.symmulgt.transmul", "astar.symmullt.transmul", "idastar.symmulgt.transmul", "idastar.symmullt.transmul" ], [ [ "78", "0", "0", "0" ], [ "0", "84", "0", "0" ], [ "0", "0", "157", "0" ], [ "0", "0", "0", "208" ] ] ] }, { "name": "stacks", "index": "0", "type": "numeric", "distinct": "10", "missing": "0", "min": "4", "max": "20", "mean": "12", "stdev": "6" }, { "name": "tiers", "index": "1", "type": "numeric", "distinct": "4", "missing": "0", "min": "5", "max": "8", "mean": "6", "stdev": "1" }, { "name": "stack.tier.ratio", "index": "2", "type": "numeric", "distinct": "17", "missing": "0", "min": "0", "max": "2", "mean": "1", "stdev": "0" }, { "name": "container.density", "index": "3", "type": "numeric", "distinct": "7", "missing": "0", "min": "1", "max": "1", "mean": "1", "stdev": "0" }, { "name": "empty.stack.pct", "index": "4", "type": "numeric", "distinct": "15", "missing": "0", "min": "0", "max": "0", "mean": "0", "stdev": "0" }, { "name": "overstowing.stack.pct", "index": "5", "type": "numeric", "distinct": "22", "missing": "0", "min": "1", "max": "1", "mean": "1", "stdev": "0" }, { "name": "overstowing.2cont.stack.pct", "index": "6", "type": "numeric", "distinct": "34", "missing": "0", "min": "1", "max": "1", "mean": "1", "stdev": "0" }, { "name": "group.same.min", "index": "7", "type": "numeric", "distinct": "2", "missing": "0", "min": "0", "max": "1", "mean": "0", "stdev": "1" }, { "name": "group.same.max", "index": "8", "type": "numeric", "distinct": "12", "missing": "0", "min": "1", "max": "14", "mean": "4", "stdev": "3" }, { "name": "group.same.mean", "index": "9", "type": "numeric", "distinct": "13", "missing": "0", "min": "1", "max": "5", "mean": "2", "stdev": "2" }, { "name": "group.same.stdev", "index": "10", "type": "numeric", "distinct": "139", "missing": "0", "min": "0", "max": "3", "mean": "1", "stdev": "1" }, { "name": "top.good.min", "index": "11", "type": "numeric", "distinct": "8", "missing": "0", "min": "1", "max": "8", "mean": "2", "stdev": "1" }, { "name": "top.good.max", "index": "12", "type": "numeric", "distinct": "31", "missing": "0", "min": "5", "max": "36", "mean": "15", "stdev": "6" }, { "name": "top.good.mean", "index": "13", "type": "numeric", "distinct": "281", "missing": "0", "min": "3", "max": "17", "mean": "8", "stdev": "3" }, { "name": "top.good.stdev", "index": "14", "type": "numeric", "distinct": "484", "missing": "0", "min": "1", "max": "12", "mean": "4", "stdev": "2" }, { "name": "overstowage.pct", "index": "15", "type": "numeric", "distinct": "69", "missing": "0", "min": "0", "max": "1", "mean": "0", "stdev": "0" }, { "name": "bflb", "index": "16", "type": "numeric", "distinct": "49", "missing": "0", "min": "8", "max": "72", "mean": "30", "stdev": "14" }, { "name": "left.density", "index": "17", "type": "numeric", "distinct": "215", "missing": "0", "min": "0", "max": "1", "mean": "0", "stdev": "0" }, { "name": "tier.weighted.groups", "index": "18", "type": "numeric", "distinct": "522", "missing": "0", "min": "0", "max": "1", "mean": "0", "stdev": "0" }, { "name": "avg.l1.top.left.lg.group", "index": "19", "type": "numeric", "distinct": "218", "missing": "0", "min": "0", "max": "1", "mean": "1", "stdev": "0" }, { "name": "cont.empty.grt.estack", "index": "20", "type": "numeric", "distinct": "62", "missing": "0", "min": "0", "max": "0", "mean": "0", "stdev": "0" }, { "name": "pct.bottom.pct.on.top", "index": "21", "type": "numeric", "distinct": "22", "missing": "0", "min": "0", "max": "1", "mean": "0", "stdev": "0" }, { "name": "row_id", "index": "23", "type": "string", "distinct": "527", "missing": "0", "identifier": "1" } ], "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 }