breast cancer train

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.n the 3-dimensional space is that described in: [K. P. Bennett and O. L. Mangasarian: "Robust Linear Programming Discrimination of Two Linearly Inseparable Sets", Optimization Methods and Software 1, 1992, 23-34].This database is also available through the UW CS ftp server:ftp ftp.cs.wisc.educd math-prog/cpo-dataset/machine-learn/WDBC/Also can be found on UCI Machine Learning Repository: https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+(Diagnostic)本数据集的特征由乳腺肿块细针穿刺抽吸（Fine Needle Aspirate, FNA）样本的数字化图像计算得到，这些特征刻画了图像中细胞核的各项属性。该数据集的特征空间为三维空间，其定义源自以下文献：[K. P. Bennett与O. L. Mangasarian：《两类线性不可分样本的鲁棒线性规划判别》，《优化方法与软件》1卷，1992年，第23-34页]。该数据集亦可通过威斯康星大学计算机科学系FTP服务器获取：登录ftp.cs.wisc.edu，进入目录math-prog/cpo-dataset/machine-learn/WDBC/。此外，该数据集还可在UCI机器学习库中获取，对应链接为：https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+(Diagnostic)