{"data_set_description":{"id":"1510","name":"wdbc","version":"1","description":"**Author**: William H. Wolberg, W. Nick Street, Olvi L. Mangasarian    \n**Source**: [UCI](https:\/\/archive.ics.uci.edu\/ml\/datasets\/breast+cancer+wisconsin+(original)), [University of Wisconsin](http:\/\/pages.cs.wisc.edu\/~olvi\/uwmp\/cancer.html) - 1995  \n**Please cite**: [UCI](https:\/\/archive.ics.uci.edu\/ml\/citation_policy.html)     \n\n**Breast Cancer Wisconsin (Diagnostic) Data Set (WDBC).** Features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. They describe characteristics of the cell nuclei present in the image. The target feature records the prognosis (benign (1) or malignant (2)). [Original data available here](ftp:\/\/ftp.cs.wisc.edu\/math-prog\/cpo-dataset\/machine-learn\/cancer\/) \n\nCurrent dataset was adapted to ARFF format from the UCI version. Sample code ID's were removed.  \n\n! Note that there is also a related Breast Cancer Wisconsin (Original) Data Set with a different set of features, better known as [breast-w](https:\/\/www.openml.org\/d\/15).\n\n\n### Feature description  \n\nTen real-valued features are computed for each of 3 cell nuclei, yielding a total of 30 descriptive features. See the papers below for more details on how they were computed. The 10 features (in order) are:  \n\na) radius (mean of distances from center to points on the perimeter)  \nb) texture (standard deviation of gray-scale values)  \nc) perimeter  \nd) area  \ne) smoothness (local variation in radius lengths)  \nf) compactness (perimeter^2 \/ area - 1.0)  \ng) concavity (severity of concave portions of the contour)  \nh) concave points (number of concave portions of the contour)  \ni) symmetry  \nj) fractal dimension (\"coastline approximation\" - 1)  \n\n### Relevant Papers   \n\nW.N. Street, W.H. Wolberg and O.L. Mangasarian. Nuclear feature extraction for breast tumor diagnosis. IS&T\/SPIE 1993 International Symposium on Electronic Imaging: Science and Technology, volume 1905, pages 861-870, San Jose, CA, 1993. \n\nO.L. Mangasarian, W.N. Street and W.H. Wolberg. Breast cancer diagnosis and prognosis via linear programming. Operations Research, 43(4), pages 570-577, July-August 1995.","description_version":"3","format":"ARFF","upload_date":"2015-05-26T16:24:07","licence":"Public","url":"https:\/\/openml.org\/data\/v1\/download\/1592318\/wdbc.arff","parquet_url":"https:\/\/data.openml.org\/datasets\/0000\/1510\/dataset_1510.pq","file_id":"1592318","default_target_attribute":"Class","tag":["Biology","cancer","Health","medical","Medicine","OpenML-CC18","OpenML100","Research","study_123","study_135","study_14","study_52","study_7","study_98","study_99","uci"],"visibility":"public","status":"active","processing_date":"2018-10-03 21:41:34","md5_checksum":"7aa183d3657e364911ced0cbd6b272bd"}}