The Classification of Breast Cancer with Machine Learning Techniques

被引：0

作者：

Kolay, Nurdan ^{[1
]}

Erdogmus, Pakize ^{[2
]}

机构：

[1] Duzce Univ, Bilgisayar Muhendisligi Bolumu, Duzce, Turkey

[2] Duzce Univ, Bilgisayar Muhendisligi Bolumu, Ogretim Uyesi, Duzce, Turkey

来源：

2016 ELECTRIC ELECTRONICS, COMPUTER SCIENCE, BIOMEDICAL ENGINEERINGS' MEETING (EBBT) | 2016年

关键词：

Machine Learning; Breast Cancer; K-means clustering; Fuzzy C-means; Support Vector Machines; PREDICTION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this study, it is aimed to classify breast cancer data attained from UCI(University of California-Irvine), Machine Learning Laboratory with some Machine Learning Techniques. With this aim, clustering performance of some distance measures in Matlab(C) has been compared, using breast cancer data. Later without using any pre-processing, some of the machine learning techniques are used for the clustering breast cancer data, using WEKA data mining software(C). As a result, it has been seen that distance measures effects the clustering performance nearly 12 percentage and the succes of the classification varies from % 45 to % 79, according to the methods.

引用

页数：4

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