{ "data_id": "22", "name": "mfeat-zernike", "exact_name": "mfeat-zernike", "version": 1, "version_label": "1", "description": "**Author**: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology \r\n**Source**: [UCI](https:\/\/archive.ics.uci.edu\/ml\/datasets\/Multiple+Features) - 1998 \r\n**Please cite**: [UCI](https:\/\/archive.ics.uci.edu\/ml\/citation_policy.html) \r\n\r\n**Multiple Features Dataset: Zernike** \r\nOne of a set of 6 datasets describing features of handwritten numerals (0 - 9) extracted from a collection of Dutch utility maps. Corresponding patterns in different datasets correspond to the same original character. 200 instances per class (for a total of 2,000 instances) have been digitized in binary images. \r\n\r\nIn this dataset, these digits are represented in terms of 47 Zernike moments. \r\n\r\n### Attribute Information \r\nThe attributes represent 47 rotation invariant Zernike moments. They can't distinguish samples of class '6' from those of class '9'. More information on Zernike moments can be found in: \r\nA. Khotanzad and Y.H. Hong: Rotation invariant pattern recognition using Zernike moments. Int. Conf. on Pattern Recognition, Rome 1998, pp. 326-328.\r\n\r\n### Relevant Papers \r\nA slightly different version of the database is used in \r\nM. van Breukelen, R.P.W. Duin, D.M.J. Tax, and J.E. den Hartog, Handwritten digit recognition by combined classifiers, Kybernetika, vol. 34, no. 4, 1998, 381-386.\r\n \r\nThe database as is is used in: \r\nA.K. Jain, R.P.W. Duin, J. Mao, Statistical Pattern Recognition: A Review, IEEE Transactions on Pattern Analysis and Machine Intelligence archive, Volume 22 Issue 1, January 2000 ", "format": "ARFF", "uploader": "Jan van Rijn", "uploader_id": 1, "visibility": "public", "creator": "Robert P.W. Duin", "contributor": null, "date": "2014-04-06 23:21:00", "update_comment": null, "last_update": "2014-04-06 23:21:00", "licence": "Public", "status": "active", "error_message": null, "url": "https:\/\/www.openml.org\/data\/download\/22\/dataset_22_mfeat-zernike.arff", "kaggle_url": null, "default_target_attribute": "class", "row_id_attribute": null, "ignore_attribute": null, "runs": 34884, "suggest": { "input": [ "mfeat-zernike", "One of a set of 6 datasets describing features of handwritten numerals (0 - 9) extracted from a collection of Dutch utility maps. Corresponding patterns in different datasets correspond to the same original character. 200 instances per class (for a total of 2,000 instances) have been digitized in binary images. In this dataset, these digits are represented in terms of 47 Zernike moments. ### Attribute Information The attributes represent 47 rotation invariant Zernike moments. They can't distingu " ], "weight": 5 }, "qualities": { "NumberOfInstances": 2000, "NumberOfFeatures": 48, "NumberOfClasses": 10, "NumberOfMissingValues": 0, "NumberOfInstancesWithMissingValues": 0, "NumberOfNumericFeatures": 47, "NumberOfSymbolicFeatures": 1, "MaxStdDevOfNumericAtts": 124.19249364407266, "MinorityClassPercentage": 10, "PercentageOfNumericFeatures": 97.91666666666666, "Quartile3MeansOfNumericAtts": 126.83265674023002, "CfsSubsetEval_DecisionStumpAUC": 0.8614040277777776, "RandomTreeDepth2AUC": 0.7797222222222222, "J48.00001.ErrRate": 0.3195, "MeanAttributeEntropy": null, "MinorityClassSize": 200, "PercentageOfSymbolicFeatures": 2.083333333333333, "Quartile3MutualInformation": null, "CfsSubsetEval_DecisionStumpErrRate": 0.314, "RandomTreeDepth2ErrRate": 0.3965, "J48.00001.Kappa": 0.645, "MeanKurtosisOfNumericAtts": 0.7353956813037765, "NaiveBayesAUC": 0.9590269444444445, "Quartile1AttributeEntropy": null, "Quartile3SkewnessOfNumericAtts": 1.2548334728305888, 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