Design and Development of Cancer Prediction using Machine Learning Technology System

Breast cancer is one of the utmost shared disease in women, classifying and predicting it is a vibrant research issue. Various machine learning system have been utilized to create different cancer models. Among various algorithms, Support Vector Machines and k nearest neighbors have been appeared to outnumber other algorithms. Though there are few studies concentrated on examining the performance of different classification algorithms .The motive of this paper is to evaluate the performance of SVM and KNN on breast cancer dataset. The cancer dataset (Wisconsin Dataset) is taken from UCI machine Repository, place for machine learning and insight Framework. The precision, accuracy F-measures of different classification algorithms are looked at. The outcome shows that SVM classifier can give the better result for classification, while accuracy of the algorithm is improved by modifying the attributes of the dataset.