{ "data_id": "1458", "name": "arcene", "exact_name": "arcene", "version": 1, "version_label": null, "description": "**Author**: \n**Source**: UCI\n**Please cite**: \n\nARCENE's task is to distinguish cancer versus normal patterns from mass-spectrometric data. This is a two-class classification problem with continuous input variables. This dataset is one of 5 datasets of the NIPS 2003 feature selection challenge.\n\nSource:\n a. Original owners \nThe data were obtained from two sources: The National Cancer Institute (NCI) and the Eastern Virginia Medical School (EVMS). All the data consist of mass-spectra obtained with the SELDI technique. The samples include patients with cancer (ovarian or prostate cancer), and healthy or control patients. \n\nb. Donor of database \nThis version of the database was prepared for the NIPS 2003 variable and feature selection benchmark by Isabelle Guyon, 955 Creston Road, Berkeley, CA 94708, USA (isabelle '@' clopinet.com). \n\nData Set Information:\nARCENE was obtained by merging three mass-spectrometry datasets to obtain enough training and test data for a benchmark. The original features indicate the abundance of proteins in human sera having a given mass value. Based on those features one must separate cancer patients from healthy patients. We added a \n number of distractor feature called 'probes' having no predictive power. The order of the features and patterns were randomized. 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