The classification of breast cancer with Machine Learning Techniques
Nurdan Kolay, Pakize Erdoğmuş · 2016
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© 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©. As a result, it has been seen that distance measures effects the clustering performance nearly 12 percentage and the success of the classification varies from %45 to %79, according to the methods.