Breast Cancer Detection Using Various Classification Algorithms

Abstract

     Machine learning algorithms are playing an important role, nowadays, to extract the features of any application. Here used these mechanisms to detect breast cancer by considering the standard dataset. Various classification techniques are considered to find the performance of the detected results. Initially removed the noise over a data set that is missed data and then extracted the features and next applied the classifiers such as SVM, KNN, Random Forest, decision tree, etc. The classifier efficiency was evaluated by considering the characteristics like true positive, false positive, ROC curve, etc. The main strength of this work is experimental results which are shown by considering the standard dataset from Kaggle.