Diagnosis of Breast Cancer Pathology on the Wisconsin Dataset with the Help of Data Mining Classification and Clustering Techniques

Abstract

Breast cancer must be addressed by a multidisciplinary team aiming at the patient’s comprehensive treatment. Recent advances in science make it possible to evaluate tumor staging and point out the specific treatment. However, these advances must be combined with the availability of resources and the easy operability of the technique. This study is aimed at distinguishing and classifying benign and malignant cells, which are tumor types, from the data on the Wisconsin Diagnostic Breast Cancer (WDBC) dataset by applying data mining classification and clustering techniques with the help of the Weka tool. In addition, various algorithms and techniques used in data mining were measured with success percentages, and the most successful ones on the dataset were determined and compared with each other.

Öznitelik Seçimi ile Desteklenen Makine Öğrenmesine Dayalı Göğüs Kanserinin Erken Tespiti ve Teşhisi

“…Çalışmada K en yakın komşu (K-nearest neighbor-KNN) ve destek vektör makinası (Support vector machine-SVM) gibi farklı modeller ile eğitimler yapılmıştır. En yüksek doğruluk oranı SVM ile %97,70 olarak elde edilmiştir [24]. Bu veri kümesinin kullanıldığı diğer bir çalışmada SVM, KNN ve random forest gibi modeller ile eğitim yapılmıştır.…”

Improving the accuracy of Covid-19 disease diagnosis with an improved fuzzy chaotic forest algorithm, optimal feature selection and decision tree

“…In some cases, different artificial intelligence techniques are sometimes combined to introduce an efficient method for medical science. The combination of image processing and deep learning can be a good example for this explanation [13,14]. The use of image processing in medical science is common for disease diagnosis [7], but considering the cost and possible complications for patients, using data mining and focusing on clinical data can be an alternative method [7].…”

Retracted: Diagnosis of Breast Cancer Pathology on the Wisconsin Dataset with the Help of Data Mining Classification and Clustering Techniques

“…This article has been retracted by Hindawi, as publisher, following an investigation undertaken by the publisher [1]. This investigation has uncovered evidence of systematic manipulation of the publication and peer-review process.…”