{ "data_id": "36", "name": "monks-problems-2", "exact_name": "monks-problems-2", "version": 1, "version_label": null, "description": "**Author**: Sebastian Thrun \n**Source**: [original](https:\/\/archive.ics.uci.edu\/ml\/datasets\/MONK's+Problems) - October 1992 \n**Please cite**: \n\nThe Monk's Problems: Problem 2 \n\nThis is a merged version of the separate train and test set which are usually distributed. On OpenML this train-test split can be found as one of the possible tasks. \n\nSources: \n(a) Donor: Sebastian Thrun School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213, USA E-mail: thrun@cs.cmu.edu \n(b) Date: October 1992 \n\nRelevant Information: The MONK's problem were the basis of a first international comparison of learning algorithms. The result of this comparison is summarized in \"The MONK's Problems - A Performance Comparison of Different Learning algorithms\" by S.B. Thrun, J. Bala, E. Bloedorn, I. Bratko, B. Cestnik, J. Cheng, K. De Jong, S. Dzeroski, S.E. Fahlman, D. Fisher, R. Hamann, K. Kaufman, S. Keller, I. Kononenko, J. Kreuziger, R.S. Michalski, T. Mitchell, P. Pachowicz, Y. Reich H. Vafaie, W. Van de Welde, W. Wenzel, J. Wnek, and J. Zhang has been published as Technical Report CS-CMU-91-197, Carnegie Mellon University in Dec. 1991. One significant characteristic of this comparison is that it was performed by a collection of researchers, each of whom was an advocate of the technique they tested (often they were the creators of the various methods). In this sense, the results are less biased than in comparisons performed by a single person advocating a specific learning method, and more accurately reflect the generalization behavior of the learning techniques as applied by knowledgeable users. There are three MONK's problems. The domains for all MONK's problems are the same (described below). One of the MONK's problems has noise added. For each problem, the domain has been partitioned into a train and test set. \n\nAttribute information: \n1. class: 0, 1 \n2. a1: 1, 2, 3 \n3. a2: 1, 2, 3 \n4. a3: 1, 2 \n5. a4: 1, 2, 3 \n6. a5: 1, 2, 3, 4 \n7. a6: 1, 2 \n\n8. Target Concepts associated to the MONK's problem: \nMONK-1: (a1 = a2) or (a5 = 1) \nMONK-2: EXACTLY TWO of {a1 = 1, a2 = 1, a3 = 1, a4 = 1, a5 = 1, a6 = 1} \nMONK-3: (a5 = 3 and a4 = 1) or (a5 \/= 4 and a2 \/= 3) (5% class noise added to the training set)", "format": "ARFF", "uploader": "Joaquin Vanschoren", "uploader_id": 2, "visibility": "public", "creator": "\"Sebastian Thrun\"", "contributor": null, "date": "2014-08-26 17:29:02", "update_comment": null, "last_update": "2014-08-26 17:29:02", "licence": "Public", "status": "active", "error_message": null, "url": "https:\/\/www.openml.org\/data\/download\/52237\/php4fATLZ", "default_target_attribute": "class", "row_id_attribute": null, "ignore_attribute": null, "runs": 0, "suggest": { "input": [ "monks-problems-2", "The Monk's Problems: Problem 2 This is a merged version of the separate train and test set which are usually distributed. On OpenML this train-test split can be found as one of the possible tasks. 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