Using Machine Learning algorithms for breast cancer risk prediction and diagnosis

被引：0

作者：

Bharat, Anusha ^{[1
]}

Pooja, N. ^{[1
]}

Reddy, R. Anishka ^{[1
]}

机构：

[1] Ramaiah Inst Technol, Dept Telecommun Engn, Bangalore, Karnataka, India

来源：

2018 3RD INTERNATIONAL CONFERENCE ON CIRCUITS, CONTROL, COMMUNICATION AND COMPUTING (I4C) | 2018年

关键词：

Breast Cancer; knn; naives bayes; CART; SVM;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Machine learning is frequently used in medical applications such as detection of the type of cancerous cells. Breast cancer represents one of the diseases that causes a high number of deaths every year. It is the most common type of cancer and the main cause of women's deaths worldwide. The cancerous cells are classified as Benign (B) or Malignant (M). There are many algorithms for classification and prediction of breast cancer: Support Vector Machine (SVM), Decision Tree (CARD, Naive Bayes (NB) and k Nearest Neighbours (kNN). In this project, Support Vector Machine (SVM) on the Wisconsin Breast Cancer dataset is used The dataset is also trained with the other algorithms: KNN, Naives Bayes and CART and the accuracy of prediction for each algorithm is compared.

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页数：4

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