{ "data_id": "98", "name": "LED-display-domain-7digit", "exact_name": "LED-display-domain-7digit", "version": 1, "version_label": "1", "description": "1. Title of Database: LED display domain\n\n2. Sources:\n (a) Breiman,L., Friedman,J.H., Olshen,R.A., & Stone,C.J. (1984). \n Classification and Regression Trees. Wadsworth International\n Group: Belmont, California. (see pages 43-49).\n (b) Donor: David Aha \n (c) Date: 11\/10\/1988\n\n3. Past Usage: (many)\n 1. CART book (above):\n -- Optimal Bayes classification rate: 74%\n -- CART decision tree algorithm: 71% (resubstitution estimate)\n -- Nearest Neighbor Algorithm: 71%\n -- 200 training and 5000 test instances\n \n 2. Quinlan,J.R. (1987). Simplifying Decision Trees. In International\n Journal of Man-Machine Studies (to appear).\n -- C4 decision tree algorithm: 72.6% (using pessimistic pruning)\n -- 2000 training and 500 test instances\n 3. Tan,M. & Eshelman,L. (1988). Using Weighted Networks to Represent\n Classification Knowledge in Noisy Domains. In Proceedings of the\n 5th International Conference on Machine Learning, 121-134, Ann\n Arbor, Michigan: Morgan Kaufmann. \n -- IWN system: 73.3% (using the And-OR classification algorithm)\n -- 400 training and 500 test cases\n\n4. Relevant Information Paragraph:\n This simple domain contains 7 Boolean attributes and 10 concepts,\n the set of decimal digits. Recall that LED displays contain 7\n light-emitting diodes -- hence the reason for 7 attributes. The\n problem would be easy if not for the introduction of noise. In\n this case, each attribute value has the 10% probability of having\n its value inverted. \n\n It's valuable to know the optimal Bayes rate for these databases.\n In this case, the misclassification rate is 26% (74% classification\n accuracy).\n \n5. Number of Instances: 500. But in the original URL you can find a C script and run it choosing the number of instances to be generated.\n\n6. Number of Attributes: 7 (all Boolean-valued)\n\n7. Attribute Information:\n -- All attribute values are either 0 or 1, according to whether\n the corresponding light is on or not for the decimal digit.\n -- Each attribute (excluding the class attribute, which is an\n integer ranging between 0 and 9 inclusive) has a 10% percent\n chance of being inverted.\n\n8. Missing Attribute Values: None\n\n9. Class Distribution: 10% (Theoretical)\n -- Each concept (digit) has the same theoretical probability\n distribution. The program randomly selects the attribute.", "format": "ARFF", "uploader": "Rafael G. 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": 13, "suggest": { "input": [ "LED-display-domain-7digit", "1. Title of Database: LED display domain 2. Sources: (a) Breiman,L., Friedman,J.H., Olshen,R.A., & Stone,C.J. (1984). Classification and Regression Trees. Wadsworth International Group: Belmont, California. (see pages 43-49). (b) Donor: David Aha (c) Date: 11\/10\/1988 3. Past Usage: (many) 1. CART book (above): -- Optimal Bayes classification rate: 74% -- CART decision tree algorithm: 71% (resubstitution estimate) -- Nearest Neighbor Algorithm: 71% -- 200 training and 5000 test instances 2. 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