breast cancer test

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.<br>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:<br>ftp ftp.cs.wisc.edu<br>cd 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)<br>

本数据集的特征提取自乳腺肿块细针抽吸活检（fine needle aspirate, FNA）的数字化图像，用于描述图像中存在的细胞核的各项特征。相关三维空间的定义源自以下文献：[K. P. 贝内特与O. L. 曼加萨里安：《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》第1卷，1992年，第23-34页]。该数据集亦可通过威斯康星大学（UW）计算机科学系（CS）FTP服务器获取：<br>ftp ftp.cs.wisc.edu<br>cd math-prog/cpo-dataset/machine-learn/WDBC/。此外，该数据集也可在UCI机器学习存储库（UCI Machine Learning Repository）中获取：https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+(Diagnostic)