Classification and Diagnostic Prediction of Breast Cancers via Different Classifiers
Journal Title: International Scientific and Vocational Studies Journal - Year 2018, Vol 2, Issue 2
Abstract
Cancer is one of the leading causes of human death in the world and has caused the death of approximately 9.6 million people in 2018. Breast cancer is the most important cause of cancer deaths in women. However, breast cancer is a type of cancer that can be treated when diagnosed early. The aim of this study is to identify cancer early in life. In this study, early diagnosis and treatment were performed by using machine learning methods. The characteristics of the people included in the Wisconsin Diagnostic Breast Cancer (WDBC) data set were classified by support vector machines (SVM), k-nearest neighborhood, Naive Bayes, J48 and random forests methods. The preprocessing step was applied to the data set prior to classification. After the preprocessing stage, 5 different classifiers were applied to the data using 10-fold cross-validation method. Accuracy, sensitivity, specificity values and confusion matrices were used to measure the success of the methods. As a result of the application, it was found that SVM with linear kernel was the most successful method with 98.24% success rate. Although it was a very simple method, the second most successful method was the k-nearest neighborhood method with a success rate of 97.72%. When the results obtained from feature selection are evaluated, it is seen that feature selection and other preprocessing methods increase the success of the system. It can be said that the success achieved in comparison with previous studies is at a good level.
Authors and Affiliations
Ahmet Saygılı
Keywords
Related Articles
- EP ID EP35731
- DOI -
- Views 434
- Downloads 0
Strategies That Transform the Retail
The objective of the present investigation is to analyze the strategies that the companies implement and the changes that originate in the retail trade and the retail trade and in the commercial establishments in the dev...
Complementary Coded Waveforms Sets in Marine Radar Application
Complementary coded waveform and mismatched filter pairs sets are used. On the contrary with Golays matched waveform filter pair the mismatched waveform filter pair does exist for all N (number pulses in waveform). Using...
Performance Analysis of Storage, Grid Connected Hybrid Photovoltaic System
Photovoltaic solar energy plants are rapidly increasing. These systems are generally on-grid or off-grid photovoltaic systems. In this study, a hybrid system is realized and analyzed. This system contains feature of on-g...
Forecasting of Electricity Generation Shares by Fossil Fuels Using Artificial Neural Network and Regression Analysis in Turkey
This study is conducted to get predictions for the generation of electricity by annual production shares and decide the most suitable method for future periods. Between 2010-2017 in Turkey, the relation of generation sha...
Solar Cell Usage in a House in Erdemli District of Mersin for Meeting Electricity Demand and Cost Analysis
Energy is the one of the basic needs in order to survive since human existence. The vast majority of this energy is derived from fosil fuels. The increase in energy demand, the limited resources, and harmful effect of di...