Breast-Cancer-Wisconsin-Anomaly-Diagnosis
所属分类：特征抽取
开发工具：Jupyter Notebook
文件大小：1293KB
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上传日期：2022-03-18 08:59:19
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sh-1993
说明： 对具有10个细胞核特征（半径、纹理等）的数字化质量图像进行统计EDA和归一化分析...
(Performed statistical-EDA and normalization analysis on digitized mass images with 10 nuclei features (radius, texture) Predicted malignant - benign cancer using Logistic, LDA-QDA, KNN, Lasso-Ridge classifiers with 0.89, 0.88, 0.92, 0.96 and 0.97 accuracies respectively along with decision boundaries and ROC curves)
文件列表:
LICENSE (1071, 2022-03-18)
PS4_Vaddy_VenkatSrinidhi.ipynb (1774553, 2022-03-18)
wdbc.data (124103, 2022-03-18)
wdbc.names (4708, 2022-03-18)
# Breast-Cancer-Wisconsin-Anomaly-Diagnosis
Performed statistical-EDA and normalization analysis on digitized mass images with 10 nuclei features (radius, texture)
Predicted malignant - benign cancer using Logistic, LDA-QDA, KNN, Lasso-Ridge classifiers with 0.89, 0.88, 0.92, 0.96
and 0.97 accuracies respectively along with decision boundaries and ROC curves
Source Information
a) Creators of data:
Dr. William H. Wolberg, General Surgery Dept., University of Wisconsin, Clinical Sciences Center, Madison, WI 53792
wolberg@eagle.surgery.wisc.edu
W. Nick Street, Computer Sciences Dept., University of Wisconsin, 1210 West Dayton St., Madison, WI 53706
street@cs.wisc.edu
Olvi L. Mangasarian, Computer Sciences Dept., University of Wisconsin, 1210 West Dayton St., Madison, WI 53706
olvi@cs.wisc.edu
Relevant information
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. A few of the images can be found at http://www.cs.wisc.edu/~street/images/
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