{ "data_id": "206", "name": "triazines", "exact_name": "triazines", "version": 1, "version_label": "1", "description": "**Author**: \n**Source**: Unknown - \n**Please cite**: \n\nThe problem is to learn a regression equation\/rule\/tree to predict the\n activity from the descriptive structural attributes. The data and\n methodology is described in detail in: - King, Ross .D., Hurst,\n Jonathan. D., and Sternberg, Michael.J.E. A comparison of artificial\n intelligence methods for modelling QSARs Applied Artificial\n Intelligence, 1994 (in press). - Hurst, Jonathan. D., King, Ross\n .D. and Sternberg, Michael.J.E. Quantitative Structure-Activity\n Relationships by neural networks and inductive logic programming:\n 2. The inhibition of dihydrofolate reductase by triazines. Journal of\n Computer Aided Molecular Design, 1994 (in press).\n \n Original source: ?. \n Source: collection of regression datasets by Luis Torgo (ltorgo@ncc.up.pt) at\n http:\/\/www.ncc.up.pt\/~ltorgo\/Regression\/DataSets.html\n Characteristics: 186 cases; 61 continuous variables", "format": "ARFF", "uploader": "Jan van Rijn", "uploader_id": 1, "visibility": "public", "creator": null, "contributor": null, "date": "2014-04-23 13:17:16", "update_comment": null, "last_update": "2014-04-23 13:17:16", "licence": "Public", "status": "active", "error_message": null, "url": "https:\/\/www.openml.org\/data\/download\/3643\/dataset_2192_triazines.arff", "kaggle_url": null, "default_target_attribute": "activity", "row_id_attribute": null, "ignore_attribute": null, "runs": 5, "suggest": { "input": [ "triazines", "The problem is to learn a regression equation\/rule\/tree to predict the activity from the descriptive structural attributes. The data and methodology is described in detail in: - King, Ross .D., Hurst, Jonathan. D., and Sternberg, Michael.J.E. A comparison of artificial intelligence methods for modelling QSARs Applied Artificial Intelligence, 1994 (in press). - Hurst, Jonathan. D., King, Ross .D. and Sternberg, Michael.J.E. 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