The Statistical Classification of Breast Cancer Data

Subhash Bagui1; Sikha Bagui2; Rohan Hemasinha1

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The Statistical Classification of Breast Cancer Data

机译：乳腺癌数据的统计分类

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摘要

In this article, we study the statistical classification of breast cancer of two well-known large breast cancer databases. We use various classification rules, such as linear, quadratic, logistic, k nearest neighbor (k-NN), and k rank nearest neighbor (k-RNN) rules and compare the performances. We also conduct feature analysis for both data sets using logistic regression model.

机译：在本文中，我们研究了两个著名的大型乳腺癌数据库的乳腺癌统计分类。我们使用各种分类规则，例如线性，二次，对数，k最近邻（k-NN）和k级最近邻（k-RNN）规则，并比较性能。我们还使用逻辑回归模型对两个数据集进行特征分析。

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《International Journal of Statistics and Applications》 |2016年第1期|共页
作者
Subhash Bagui1; Sikha Bagui2; Rohan Hemasinha1;
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中图分类统计学;
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1. Breast cancer histological classification: agreement between the Office for National Statistics and the National Health Service Breast Screening Programme [J] . Toral Gathani, Diana Bull, Jane Green, Breast Cancer Research . 2005,第6期

机译：乳腺癌组织学分类：国家统计局和国家卫生服务局乳腺癌筛查计划之间的协议
2. Breast Cancer Statistics in Korea in 2017: Data from a Breast Cancer Registry [J] . Sang Yull Kang, Yoo Seok Kim, Zisun Kim, Journal of Breast Cancer . 2020,第2期

机译：2017年韩国乳腺癌统计：来自乳腺癌登记处的数据
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机译：基于案例的推理，神经网络和自适应神经模糊推理系统分类技术在乳腺癌数据集分类诊断中的应用。
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机译：乳腺癌分类使用统计特征和热图的模糊分类
5. Use of statistical analysis, data mining, decision analysis and cost effectiveness analysis to analyze medical data: Application to comparative effectiveness of lumpectomy and mastectomy for breast cancer. [D] . Ugiliweneza, Beatrice. 2011

机译：使用统计分析，数据挖掘，决策分析和成本效益分析来分析医学数据：在乳腺癌的乳房切除术和乳房切除术的比较有效性中的应用。
6. New statistical learning theory paradigms adapted to breast cancer diagnosis/classification using image and non-image clinical data [O] . Walker H. Land Jr., John J. Heine, Tom Raway, -1

机译：新的统计学习理论范式适用于使用图像和非图像临床数据进行乳腺癌诊断/分类
7. New statistical learning theory paradigms adapted to breast cancer diagnosis/classification using image and non-image clinical data [O] . Walker H. Land Jr., John J. Heine, Tom Raway, 2008

机译：新的统计学习理论范式适用于使用图像和非图像临床数据的乳腺癌诊断/分类
8. Constraint Satisfaction Neural Network Approach for Data Mining Classification and Association Rules in Breast Cancer Databases [R] . Tourassi, G. D. 2003

机译：基于约束满足神经网络的乳腺癌数据挖掘分类与关联规则

The Statistical Classification of Breast Cancer Data

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